NATIONAL A E R O N A U T I C S AND SPACE ADMINISTRATION The Deep Space Network Progress Report 42-29 July and August 1975 (NASA-CR-1U5923) THE DEEP SPACE NETWCFK Progress Report, Jul. - Aug. 1975 (Jet Propulsion Lab.) 216 p HC $7.75 N76-1U296 THRU Unclas G3/31 39375 J E T P R O P U L S I O N L A B O R A T O R Y C A L I F O R N I A INSTITUTE OF T E C H N O L O G Y P A S A D E N A , C A L I F O R N I A October 15, 1975 https://ntrs.nasa.gov/search.jsp?R=19760007208 2020-03-22T18:24:51+00:00Z N A T I O N A L A E R O N A U T I C S A N D S P A C E A D M I N I S T R A T I O N The Deep Space Network Progress Report 42-29 July and August 1975 J E T P R O P U L S I O N L A B O R A T O R Y C A L I F O R N I A INSTITUTE OF T E C H N O L O G Y P A S A D E N A , C A L I F O R N I A October 15, 1975 Preface Beginning with Volume XX, the Deep Space Network Progress Report changed from the Technical Report 32- series to the Progress Report 42- series. The volume number continues the sequence of the preceding issues. Thus, Progress Report 42-20 is the twentieth volume of the Deep Space Network series, and is an uninter- rupted follow-on to Technical Report 32-1526, Volume XIX. This report presents DSN progress in flight project support, tracking and data acquisition (TDA) research and technology, network engineering, hardware and software implementation, and operations. Each issue presents material in some, but not all, of the following categories in the order indicated: Description of the DSN Mission Support Ongoing Planetary/Interplanetary Flight Projects Advanced Flight Projects » Radio Science Radio Science Support Special Projects Supporting Research and Technology Tracking and Ground-Based Navigation Communications—Spacecraft/Ground Station Control and Operations Technology Network Control and Data Processing Network Engineering and Implementation Network Control System Ground Communications Deep Space Stations Operations Network Operations Network Control System Operations Ground Communications Deep Space Stations Planning and Facilities TDA Planning Facility Engineering In each issue, the part entitled "Description of the DSN" describes the functions and facilities of the DSN and may report the current configuration of one of the five DSN systems (Tracking, Telemetry, Command, Monitor and Control, and Test and Training). The work described in this report series is either performed or managed by the Tracking and Data Acquisition organization of JPL for NASA. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 III Contents DESCRIPTION OF THE DSN DSN Functions and Facilities 1 N. A. Renzetti DSN Command System Mark 111-75 W. G. Stinnett NASA Code 311-03-42-95 MISSION SUPPORT Ongoing Planetary/Interplanetary Flight Projects Viking Mission Support 10 D. J. Mudgway, A. I. Bryan, and D. W. Johnston NASA Code 311-03-21-70 Helios Mission Support 15 P. S. Goodwin, W. G. Meeks, S. E. Reed, and R. E. Morris NASA Code 311-03-21-50 SUPPORTING RESEARCH AND TECHNOLOGY Tracking and Ground-Based Navigation S-Band Zero-Delay Device Multipath Tests on the 64-Meter Antenna at DSS 43, DSS 63, and DSS 14 20 T. Y. Otoshi NASA Code 310-10-61-13 Communications—Spacecraft/Ground Calculating Acquisition Behavior for Completely Digital Phase-Locked Loops 33 J. R. Lesh NASA Code 310-20-67-08 The Effect of Noise and Diversity on Synthetic Array Radar Imagery . . 46 Z>~^ S. Butman and R. G. Lipes NASA Code 310-20-67-08 An X-Band Radiometer for the Microwave Weather Project 54 7)7 M. S. Reid, 0. B. Parham, and R. A. Gardner NASA Code 310-20-66-06 Aerodynamic Static Differential Pressure Values for the 50 Percent Porous Reflector Dish 60 ~D& M. S. Katow NASA Code!310-20-65-01 **fcECET)r\r/-i »» ^^vw PAQB JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Station Control and Operations Technology RF Automation Demonstration R. B. Crow NASA Code 310-30-68-10 66 Transmitter Automation R. M. Gosline NASA Code 310-30-68-11 Automatic Microwave Configuration Control J. G. Leflang NASA Code 310-30-68-10 Three-Dimensional Plotting on a Two-Dimensional Surface . . . . S. K. Skedzeleski NASA Code 310-30-69-08 Rapid Access Disks Utility Programs for the SDS 930 Computer . . . S. K. Skedzeleski NASA Code 310-30-69-08 Doppler Spectrum Extraction of Planetary Radar Data Using Computer FFT and Integration . D. E. Wallis NASA Code 310-30-69-08 . 74 . 80" . 83 - 86-2/0 Radar Ranging of the Planet Mars at 8495 MHz G. S. Downs and P. E. Reichley NASA Code 310-30-69-08 95 Network Control and Data Processing Automatic Control of DSS 13 K. I. Moyd NASA Code 310-40-70-04 107 NETWORK AND FACILITY ENGINEERING AND IMPLEMENTATION Network Easy Complex Number Manipulation With MBASIC . . . . C. A. Greenhall NASA Code 311 -03-42-95 115 DSN Standard Practices for Software Implementation D. C. Preska NASA Code 311-03-41-15 119 ~>C vi JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Deep Space Stations Receiver Stability ............... : . 131 ~ H. G. Nishimura and E. J. Serhal, Jr. NASA Code 311-03-42-48 Effect of Phase Distortion on Effective Signal Power— A Simple Mathematical Model .............. 136 J. I. Molinder NASA Code 311-03-42-95 Goldstone Wind Speeds for the SENSMOD Program ....... 141-X R. Levy and G. Lorden NASA Code 31 1-03-41-08 Meteorological Monitoring Assembly ............ 152~\ H. Burnell, H. Phillips, and R. Zanteson NASA Code 31 1-03-42-54 The Minimanual: A New Concept in Operation and Maintenance ^ Handbooks . . . . . . . . . . . . . . . . . . . 160"^ J. Nathenson NASA Code 31 1-03-42-95 Automatic Control Techniques Used on 64-Meter-Diameter ., Antenna Power Systems ............... 164 ~'\ J. Dorman NASA Code 311-03-41-14 Upgrade of Heating System for Energy Conservation at DSS 62, Cebreros, Spain .................. 177~X J. M. Urech NASA Code 312-03-15-00 OPERATIONS Network Operations Pseudo-DRVID: A New Technique for Near-Real-Time Validation of Ranging System Data ............... 180 A. L. Berman NASA Code 31 1-03-13-20 Automatic Total Recall System Test Program ......... 188 G. L. Mock NASA Code 311-03-14-42 Operations Analysis of Intermediate Data Record Production in the Viking Era . . D. C. Card NASA Code 311-03-14-52 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 yjj PROGRAM PLANNING Quality Assurance Coordinate Measuring Machine and Programmable Calculator . . . . 205 "~/\ H. A. Greth and J. Kundrat NASA Code 311-03-32-20 viii JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 N76 14297 DSN Functions and Facilities N. A. Renzetti Office of Tracking and Data Acquisition The objectives, functions, and organization of the Deep Space Network are summarized. Deep space station, ground communication, and network operations control capabilities are described. The Deep Space Network (DSN), established by the National Aeronautics and Space Administration (NASA) Office of Tracking and Data Acquisition (OTDA) under the system management and technical direction of the Jet Propulsion Laboratory (JPL), is designed for two-way- communications with unmanned spacecraft traveling ap- proximately 16,000 km (10,000 mi) from Earth to the farthest planets of our solar system. It has provided track- ing and data acquisition support for the following NASA deep space exploration projects, for which JPL has been responsible for the project management, development of the spacecraft, and conduct of mission operations: (1) Ranger. (2) Surveyor. (3) Mariner Venus 1962. (4) Mariner Mars 1964. (5) Mariner Venus 1967. (6) Mariner Mars 1969. (7) Mariner Mars 1971. (8) Mariner Venus/Mercury 1973. The DSN has also provided tracking and data acquisi- tion support for the following projects: (1) Lunar Orbiter, for which the Langley Research Center carried out the project management, space- craft development, and mission operations func- tions. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 (2) Pioneer, for which the Ames Research Center car- ried out the project management, spacecraft devel- opment, and mission operations functions. (3) Apollo, for which the Lyndon B. Johnson Space Center was the project center and the Deep Space Network supplemented the Spaceflight Tracking and Data Network (STDN), which is managed by the Goddard Space Flight Center (GSFC). (4) Helios, a joint United States/West Germany project. (5) Viking, for which the Langley Research Center pro- vides the project management and Lander space- craft, and conducts mission operations, and for which JPL provides the Orbiter spacecraft. The Deep Space Network is one of two NASA net- works. The other, the Spaceflight Tracking and Data Network, is under the system management and technical direction of the Goddard Space Flight Center. Its function is to support manned and unmanned Earth-orbiting and lunar scientific and advanced technology satellites. Al- though the DSN was concerned with unmanned lunar spacecraft in its early years, its primary objective now and into the future is to continue its support of planetary and interplanetary flight projects. A development objective has been to keep the network capability at the state of the art of telecommunications and data handling and to support as many flight projects' as possible with a minimum of mission-dependent hard- ware and software. The DSN provides direct support to each flight project through that project's tracking and data systems. This management element is responsible for the design and operation of the hardware and software in the DSN which are required for the conduct of flight operations. As of July 1972, NASA undertook a change in the inter- face between the network and the flight projects. Since January 1, 1964, the network, in addition to consisting of the Deep Space Stations and the Ground Communications Facility, had also included the Mission Control and Com- puting Facility and had provided the equipment in the mission support areas for the conduct of mission opera- tions. The latter facilities were housed in a building at JPL known as the Space Flight Operations Facility (SFOF). The interface change was to accommodate a hardware interface between the network operations con- trol functions and the mission control and computing functions. This resulted in the flight project's picking up the cognizance of the large general-purpose digital com- puters, which were used for network processing as well as mission data processing. It also assumed cognizance of all of the equipment in the flight operations facility for display and communications necessary for the conduct of missi6n operations. The network has already undertaken the development of hardware and computer software necessary to do its network operations control and monitor functions in separate computers. This activity became known as the Network Control System implementation. A characteristic of the new interface is that the network provides direct data flow to and from the stations via appropriate ground communications equipment to Mission Operations Centers, wherever they may be; namely, metric data, science and engineering telemetry, and such network monitor data as are useful to the flight project. It accepts command data from the flight project directly into the ground communications equipment for trans- mission to the station and thence to the spacecraft in a standardized format. In carrying out its functions, the network activities can be divided into two general areas. The first includes those functions which are associated with the in-flight support and in tracking the spacecraft; its configuration can be characterized as follows: (1) DS2V Tracking System. Generates radio metric data; i.e., angles, one- and two-way doppler and range, and transmits raw data to mission control. (2) DSN Telemetry System. Receives, decodes, records, and retransmits engineering and scientific data generated in the spacecraft to Mission Control. (3) DSN Command System. Accepts coded signals from Mission Control via the Ground Communications Facility (GCF) and transmits them to the space- craft in order to initiate spacecraft functions in flight. The second category of activity supports testing, train- ing, and network operations control functions and is con- figured as follows: (1) DSN Monitor and Control System. Instruments, transmits, records, and displays those parameters of the .DSN necessary to verify configuration and validate the network. Provides operational direction and configuration control of the network and primary interface with flight project mission control personnel. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 (2) DSN Test and Training System. Generates and con- trols simulated data to support development, test, training, and fault isolation within the DSN. Partici- pates in mission simulation with flight projects. The capabilities needed to carry out the above func- tions have evolved in three technical areas: (1) The Deep Space Stations that are distributed around Earth and which, prior to 1964, formed part of the Deep Space Instrumentation Facility. The technology involved in equipping these sta- tions is strongly related to the state of the art of telecommunications and flight/ground design con- siderations and is almost completely multimission in character. Table 1 gives a description of the Deep Space Stations and the Deep Space Communica- tions Complexes (DSCCs) they comprise. (2) Ground communications. This technology supports the Earth-based point-to-point voice and data com- munications from the stations to the Network Operations Control Area at JPL, Pasadena, and to the Mission Operations Centers, wherever they may be. It is based largely on the capabilities of the common carriers throughout the world which are engineered into an integrated system by the Goddard Space Flight Center for support of all NASA programs. The term "Ground Communica- tions -Facility" is used for the sets of hardware and software needed to carry out the functions. The Network Operations Control Center is the func- tional entity for centralized operational control of the network and interfaces with the users. It has two separable functional elements; namely, Network Opera- tions Control and Network Data Processing. The functions of the Network Operations Control Cen- ter are: (1) Control and coordination of network support to meet commitments to network users. (2) Utilization of the network data processing com- puting capability to generate all standards and limits required for network operations. (3) Utilization of network data processing computing capability to analyze and validate the performance of all network systems. The personnel who carry out the above functions are on the first floor of Building 230, wherein mission operations functions are carried out by certain flight projects. Net- work personnel are directed by an Operations Control Chief. The functions of the Network Data Processing are: (1) Processing of data used by Network Operations Control for the control and analysis of the network. (2) Display in Network Operations Control Area of data processed in Network Data Processing Area. (3) Interface with communications circuits for input to and output from Network Data Processing Area. (4) Data logging and production of the intermediate data records. The personnel who carry out these functions are lo- cated in Building 202, which is approximately 200 m from Building 230. The equipment consists of minicomputers for real-time data system monitoring, two XDS Sigma 5's, display, magnetic tape recorders, and appropriate inter- face equipment with the ground data communications. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 1. Tracking and data acquisition stations of the DSN Antenna DSCC Goldstone Tidbinbilla - Madrid Location California Australia Australia Spain DSS Pioneer Echo (Venus)" Mars Weemala Ballima Honeysuckle Creek Robledo Cebreros Hobledo DSS serial - designation 11 12 13 14 42 43 44 61 62 63 Diameter, m ( f t ) 26(85) 26(85) 26(85) 64(210) 26(85) 64(210) 26(85) 26(85) 26(85) 64(210) Type of mounting Polar Polar Az-El Az-El Polar Az-El X-Y Polar Polar Az-El Year of initial operation 1958 1962 1962 1966 1965 1973 1973 1965 1967 1973 "A maintenance facility. Besides the 26-m (85-ft) diam Az-El mounted antenna, DSS 13 has a 9-m (30-ft) diam Az-El mounted antenna that is used for interstation time correlation using lunar reflection techniques, for testing the design of new equipment, and for support of ground-based radio science. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 DSN Command System Mark 111-75 W. G. Stinnett DSN Systems Engineering Office A description of the DSN Command System Mark 7/7-75 configuration is presented. The functional operation of the system is discussed, as well as a brief description of the new implementation included in the Mark 111-75 configuration. I. Introduction The DSN Command System, one of the six network systems, has almost completed the implementation of new capabilities and configurations to provide the required support to missions set for the 1975 to 1977 era. These changes will lead to completion of the Mark 111-75 configuration. These configurations and capabilities will support the ongoing Pioneers 6 through 10, Pioneer Saturn, and Helios A missions. These configurations and capabilities will further support the Viking and Helios B missions. (At the time of submittal of this article, the first Viking Orbiter-Lander spacecraft had been launched and successfully supported by the DSN Command System. The second Viking launch is imminent.) The DSN Command System Mark.III-75 configurations are shown in Fig.l. The significant changes that have occurred, or are occurring, to complete the Mark 111-75 configurations are denoted in Fig. 1. These changes are occurring in two areas: (1) The Network Operations Control Center (NOCC), and (2) The 64-meter deep space stations (DSSs). The purpose of the NOCC is to provide capabilities to control and monitor the operation of the DSN Command System in an environment where widely separated deep space stations are simultaneously support- ing different spacecraft. The Mark IH-75 NOCC will provide the control and monitoring functions. The significant changes that are occurring at the 64-meter deep space stations are: (1) the implementation of an additional receiver-exciter (Block IV), and (2) the implementation of a high-power (100-kW) transmitter at the 64-meter deep space stations in Australia and Spain. II. Data Flow and Functional Operation The data flow and functional operation of the DSN Command System can best be described by defining three periods of operation: (1) pre-track, (2) during track, and (3) post-track. The following 'paragraphs describe the opera- tion of the system during these periods. (Refer to Fig. 1 for data flow description.) A. Pre-Track Operation Prior to a spacecraft track, the DSS operations personnel perform the station countdown. This involves the selection of the equipment to be used, and the validation that a complete and correct data path has been established and that all support equipment is operating JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 within specifications. After the station countdown is complete (approximately 30 minutes prior to spacecraft acquisition), the control of the station's command functions is accomplished remotely via high-speed data messages from the NOCC. The appropriate standards and limits, corresponding to the configuration, are established via high-speed data messages. Spacecraft-dependent parameters, such as symbol period, command subcarrier frequency, exciter frequency, and appropriate abort limits, are established via these messages. After the proper configuration and standards and limits have been established, test commands are transmitted through the system to ensure that the system can accept spacecraft commands via high-speed data messages, temporarily store the commands, and properly confirm transmission. After NOCC operations personnel have established that the system is operating properly, the system is ready to. be turned over to the flight project for acceptance of actual spacecraft com- mands during the spacecraft track period. B. During Track Operation Commands generated at the Mission Operations Center are placed in high-speed data blocks and transmitted to the DSS command stack. The command stack provides storage of high-speed data blocks (stack modules) of command data. Each stack module consists of up to six command elements. Each command element contains up to 71 bits of command data and, at project option, can be either timed or nontimed. Commands can also be entered and controlled locally at the DSS via a manual input/output device at the Command Processor. A manual buffer in the Command Processor, capable of holding up to six command elements of up to 71 bits each, can be loaded via the local input/ output device or by high-speed data messages from the Mission Operations Center. The entire contents of the manual buffer or any one command element in the buffer can be transferred to the command stack. The top command element in the first stack module is eligible for transmission to the spacecraft. Nontimed commands are transmitted immediately after eligibility. Timed commands are transmitted after becoming eligible at the time specified in the high-speed data block. At the time of transmission of the command element, the Command Processor establishes the proper mode (see Fig. 2 for description of the various modes) and configuration of the Command Modulator Assembly; then the command is transferred to the Command Modulator Assembly for immediate transmission via the Receiver-Exciter, Trans- mitter, Microwave, and Antenna Subsystems. Related verification, confirmation, and abort criteria (if required) are established by the Command Processor. During these command operations, events may occur in which high-speed data message transmission to the Mission Operations Center becomes necessary. The following events initiate message transmission to the Mission Operations Center: (1) Confirmed command element. (2) Aborted command element. (3) DSS alarm or alarm clear. (4) Response to a recall. (5) High-speed data block rejection by the Command Processor. (6) Acknowledged receipt of a high-speed data block. A digital Original Data Record of DSN Command System activity is generated at the DSS. An analog record of the Command Modulator Assembly output is also generated at the DSS by the Pre-Post Detection Record- ing Subsystem. During the spacecraft track, the NOCC receives all high-speed data messages being received by and generated by the DSS. DSN Command System verification, alarm diagnosis, and displays are accomplished by the NOCC. C. Post-Track Operations At the Mission Operations Center, during the command- ing of the spacecraft, a data record is generated to provide a log of all commands transmitted to the spacecraft. The post-track operation period has been set aside to recover missing data, if, during the track, data failed to get logged on the data record. Data are extracted from the DSS Original Data Record and played back via high-speed data messages to the Mission Operations Center. The playback data are used to complete the data record at the Mission Operations Center. III. NOCC Capabilities The final configuration of the NOCC to support the Mark 111-75 Command System is planned for completion in the last quarter of calendar year 1975. The NOCC has been implemented in three phases. The first two phases included minimum mandatory functions to accomplish Command System control and monitoring. These functions in many cases were awkward and inefficient to use. The third phase of implementation improves and adds to the JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 functions provided in the first two phases. The description below includes the functions to be provided in the third phase of implementation and completes the NOCC implementation for the Mark HI-75 configuration. A. High-Speed Data Message Generation The NOCC will have the capability to generate the high-speed data messages required to be transmitted to the deep space stations. These messages include the following data: (1) Configuration. (2) Standards and limits. (3) Test commands. (4) Mode control. (5) Recall request. The first three types of data listed above contain spacecraft-unique parameters. Thus, numerous high-speed data messages are required. These messages are generally constructed and stored in advance of their use. However, the capability is provided to modify parameters within these messages for immediate transmission to a DSS. B. High-Speed Data Message Transmission Included in the capabilities at the NOCC are the functions of transmitting the high-speed messages to a DSS, verifying proper receipt at the DSS, and verifying proper processing by the DSS. C. System Validation During a spacecraft track, the NOCC monitors the operation of the system to ensure its proper functioning. Status messages from the DSS are received and processed, and displays are provided to DSN operations personnel. In the event of failure, these displays provide the necessary tools for failure isolation and system recovery. IV. DSS Capabilities As stated before, the major changes occurring to complete the Mark HI-75 Command System at the deep space stations are: (1) the implementation of an additional receiver-exciter at the 64-meter stations, and (2) the implementation of 100-kW transmitters at the deep space stations in Spain and Australia. Completion of these implementations is planned within the next few months. The additional exciter will provide redundancy to a major element in the Command System. This will increase the ability of the DSN to-provide faster command recovery times in support of the flight projects. The implementa- tion of the high-power transmitters provides a significant increase in DSN uplink capabilities, as well as providing physical redundancy to another major element in the Command System. V. Future Plans After completion of the Mark HI-75 configuration, the next major upgrade to the system is planned for support of the Mariner Jupiter/Saturn 1977 mission. Replacement of the obsolete Command Processors at the deep space stations is planned. This Mark 111-77 configuration will include dedicated Command Processors at the deep space stations (current processors are shared between the command and telemetry functions at the DSS). These new processors will greatly increase processing speed and core available for the command functions at the DSS. This will allow the DSN to provide support to missions utilizing higher command bit rate transmissions. The relatively slow processing speed and core limitations existing in the current processor do not allow bit rate transmissions required by future spacecraft. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 $Ou 5z8o 15 8 z 15 o = > Q £ z 0 S|2i|8& saet . 1 &: . _ - |z|a S JQ'-'Q o < ? o u u ^ S f . Z O u u oiiZ "r ~ - ~ .n i is - i L I 1 I Z O u < ORIGINAL OF POOR QUALITY JPL DEEP SPACE NETW ORK PROGRESS REPORT 42-29 O . ^ U J Ilsl ^ < t ^<»iZ>T g S < < 0gfw 9 9 £ ^ 5 OOCOuL AND ONLY RE DA OuoOs > ou D Y < z < z _iO _iO M te§ oCD \ \ c ) \l+2Acos06 + AV where _ -2^» (I. - II) + (2) (3) (4) (5) and A = ratio of the magnitudes of the leakage and primary signals as measured at the output port of the ZDD hom (see Fig. 1) ii,i2 — physical path lengths, respectively, of the primary and leakage paths going one-way, cm c = speed of light («*3 X 1010 cm/s) /„,/(, — uplink and downlink frequencies, respectively, Hz \l/a,\jib — phase angles of reflection coefficients (if any) in the leakage path for uplink and downlink signals, respectively, rad The exact relationship of (42 — ia) to subreflector move- ment is difficult to derive due to defocusing effects and the changes in incidence angles that differ for the pri- mary wave and the multipath wave. As a first-order approximation, (6) where AJ?0 = differential path length when the indicated subreflector position is zero, in. Si = indicated subreflector position, in.1 'The subreflector position on the equipment is indicated in inches rather than in centimeters. To be meaningful this indicated position should not be converted to the metric system. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 21 The automatic gain control (AGC) downlink signal level change observed by the ground receiver will vary ac- cording to the relationship \F T \ d B = 101og10 [(1+ 2Acos00+ A2)(l + 2Acos0f,+ A2)] (7) and the AGC signal level (in dBm) observed at the ground receiver is (8) where K2 = the AGC signal level which would be ob- served in the absence of multipath (in dBm). III. Theoretical and Experimental Data A. Subreflector Tests Figures 2 through 7 are computer printouts and plots showing a comparison of theoretical and experimental data obtained from subreflector tests at DSS 43, 63, and 14. The uplink and downlink test frequencies were ap- proximately the Helios spacecraft frequencies of 2115 and 2297 MHz, respectively. The printouts and plots were generated by a computer program to perform a least squares fit of theoretical values to experimental data. The theoretical data are based upon Eqs. (1) through (8), and a best fit is made first to the experimental ranging data to determine the best fit value of (1) true station delay Kt in the absence of multipath, (2) the differential length Ai0 as defined by Eq. (6), and (3) the relative strength of the leakage signal A expressed in decibels. The program then uses these best fit values of AJZ0 and A to calculate the theoretical AGC signal levels as a function of subreflector settings. This sequence for best fit was chosen because the range data are a result of long term averaging, while the AGC data are either typically noisier or generally lag behind real-time changes. The AGC data are also dependent upon the accuracy of the calibration curves and operation only at the signal levels where the calibration curves apply. Note from the computer printouts on Figs. 2, 4, and 6 that the best fit values of Ai0 are typically about 3327.4 cm (1310 in.). This value compares favorably with values of approximately 3332.5 cm (1312 in.) obtained from measuring physical path lengths on scaled drawings (see table in Fig. 1). From Fig. 1, it can be seen that this value is associated with a multipath wave reflected off the cone platform. The values of approximately —15 to —20 dB for Ads agree with those calculated independently by Ludwig (Ref. 7). These values are also consistent with beam efficiency values published in Ref. 8 for the portion of the beam illuminating the cone platform. An attempt to explain the higher value of about —10 dB for AdB at DSS 63 will be made later after discussion of the plotted curves. Examination of the plotted curves shows that reason- ably good agreement was obtained between theory and experiment for DSS 43 and DSS 14. The typical devia- tions in range are about 3 ns, and typical deviations in AGC are about 0.3 dB. These deviations might be due to another smaller multipath effect caused by a wave bounc- ing off the cone roof and not accounted for by the theory. The larger discrepancy for DSS 63 was previously attributed to a cone missing from the cone platform. However, it was recently learned that a cone was also missing from the cone platform on the DSS 43 antenna during 1974 and during the subreflector test. Therefore, the stronger multipath effect and larger discrepancy at DSS 63 might be due to the location of the missing cone with respect to the location of the ZDD. The ZDD loca- tions and tricone configurations at DSS 43, DSS 63, and DSS 14 for the subreflector tests are shown in Fig. 8. Note that at DSS 63 the missing cone is at Bay 1, while at DSS 43, the missing cone is at Bay 3. Because of the different locations of the missing cone with respect to the ZDD, a stronger multipath signal could exist at DSS 63 than at DSS 43. The large disagreement of calculated and experimental AGC values at DSS 63 can be explained as follows. The AGC calibrations at DSS 63 were performed in the region of —140 to —170 dBm While actual multipath tests were performed at —120 dBm. The measured signal levels for the tests were outside the calibrated region, and there- fore the measured AGC variations were much smaller than the actual variations. G. Pasero at DSS 63 stated that when the test was repeated for AGC data only at a later date in the calibrated range of the receiver, the peak-to- peak AGC variation observed was about 10 dB. This peak-to-peak variation agrees favorably with the calcu- lated values shown on the plots. All of the subreflector test results presented apply only to the antenna pointed at zenith and at the S-band test frequencies involved. Results of subreflector tests at 45 and 20 deg elevation angles have been reported in Ref. 3, but as yet no curve fit has been made to these data. 22 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 B. Antenna Tipping Test Another airpath test that is often performed is the antenna tipping test. In this test the total system range delay is continuously measured while the antenna is slowly tipped from the zenith position to the horizon. Figures 9 and 10 show the results of the tipping test for DSS 43 and DSS 63, respectively. No current tipping test data were obtained at DSS 14. The tipping tests were performed on a different day from the subreflector tests, and the measured zenith range delays differed by about 10 to 20 ns. To avoid confusion, the tipping test data were converted to show changes relative to the zenith position. A polynomial curve fit was made to the data to show trends only. The polynomial curve fit is not based on the multipath equations. However, it is interesting to note that when the antenna is tipped from the zenith position to the horizon, the subreflector moves from the normal operating point outward about 0.5 to 0.7 in. (Ref. 9). If one examines the subreflector data for DSS 43 and DSS 63, (see Figs. 3a and 5a) and moves from the operating point to a point about 0.5 in. in the positive direction, the magnitude and phase (sign) of the range change gen- erally agree with the antenna tipping data. Therefore one can assume that the phenomena associated with the antenna tipping tests are correlated to the same multipath phenomenon observed on the subreflector test. IV. Corrections to Measured Station Range Delay In the preceding section it was shown that the true station delay could be determined with the aid of a com- puter program. The definition of true range is that which would have been measured in the absence of multipath. Since the subreflector position during pre- and post-track zero-delay calibration is known and since the tine range is given by the computer program, one can calculate a correction for the measured station delay. In addition, one can predict what the observed range residuals would be between stations. For example, let BIAS'DSN — measured DSS round trip delay in the presence of multipath BIASDSN = true DSS round trip delay in the absence of multipath Using the equation in Ref. 1 the measured round-trip light time (RTLT) will be RTLT' = Rtotai - BIAS8/0 - BIAS'Dsy + Z (9) but the true RTLT is RTLT = R total - BIASS/0 - BIASDSK + Z (10) where Rtotai is the total measured range and Z is the Z-correction. If BIAS'oss, BIASoss are given in nanoseconds the range residual in meters is computed from Range Residual = [RTLT' - RTLT] [0.15] (11) (meter) (ns) (ns) Substitutions of Eqs. (9) and (10) into Eq. (11) gives Range Residual = [BIASDSli - BIAS'DStf] [0.15] (12) (meter) (ns) (ns) For DSS 43, the 1974 pre- and post-track ZDD calibra- tions were done with the subreflector at 0 in. Then from the data on Fig. 2 BIASDSK - BIAS'DSIf = 3198.4 - 3227.2 = -28.8ns Range Residual = —4.3 meters For DSS 63, the 1974 pre- and post-track ZDD calibra- tions were done with the subreflector at —0.5 in. From the data on Fig. 4, BIASDSII - BIAS ' , = 4210.8 - 4155.9DSN and = 54.9ns Range Residual = 8.2 meters Since DSS 14 does not operate in the airpath configura- tion, there is no need to compute residuals for DSS 14. It is interesting to note that the above residuals are in excellent agreement with the residuals published by Christensen for Mariner 10 at Mercury Encounter I on March 29, 1974 (Ref. 5). Unfortunately, the results pre- sented here cannot be used conclusively to explain the residuals. The main reason is that during Mariner 10 Mercury Encounter I on March 29, 1974, the ZDD horn at DSS 43 was located at the outer edge of the 64-m dish surface. The ZDD horn was moved to a new location closer to the center of the antenna on August 1, 1974 (see Fig. 8). The DSS 43 test results reported in this article were obtained at the new location. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 23 Another reason why the results may not apply to the Mariner 10 residuals is the slight differences in test fre- quencies. If one were to assume that the same multipath conditions existed at DSS 63 as during the Mariner 10 Mercury Encounter I period, calculations show that for the Mariner 10 uplink/downlink frequencies of 2.11352 GHz/2.29523 GHz, the range residual would have been + 5.0 meters. It can' generally be expected that the multipath-caused residuals will change significantly with uplink/downlink frequency changes as small as 1 or 2 MHz. Since the multipath error can change in magnitude and phase with (1) frequency, (2) ZDD horn location, or (3) the RF feed configuration, it is important to document these parameters for future reference. The test configura- tions for the tests done at DSS 43, DSS 63, and DSS 14 are shown in Fig. 8. Table 1 shows the critical param- eters of interest which if altered would invalidate the range correction data obtained. V. Summary and Recommendations for Future Work It has been shown that even though multipath effects are present on the antenna, the effect can be separated out by the movable subreflector technique. This method assumes that the dominant interaction is occurring be- tween the subreflector and the cone or its support struc- ture. If there are multipath effects outside this region, one must use a movable ZDD horn on the dish sur- face such as that described in Ref. 6. Range measure- ments made over1 a band of frequencies might also reveal multipath effects and enable identification of multipath sources. If the station periodically (every 3 months) obtains data from the subreflector test, then through the use of the computer program, one could determine the station delay more accurately. Since the computer program also assists in locating die multipath source, a simple antenna redesign might be done to eliminate the problem entirely. One solution may be to restore the hyperboloid vertex plate which is not present on 64-m antennas. Although good agreement was obtained between theory and experiment for the tests described in this article, it is still desirable to confirm the location of multipath source. Plans are being made to perform an experiment placing absorbers on the cone platform of the DSS 14 64-m antenna and seeing if the dominant multipath effect disappears for both S- and X-band. The results of this test will be reported in a future issue of this publication. References 1. TRK-2-8 Module of DSN System Requirements Detailed Interface Design Document 820-13, Rev. A, Jet Propulsion Laboratory, Pasadena, Calif., July 1, 1973 (an internal document). 2. Stelzried, C. T., Otoshi, T. Y., and Batelaan, P. D., "S/X Band Experiment: Zero Delay Device Antenna Location," in The Deep Space Network Progress Report 42-20, pp. 64-68, Jet Propulsion Laboratory, Pasadena, Calif., Apr. 15, 1974. 3. Otoshi, T. Y., and LuValle, J., "Zero Delay Device Airpath Tests at DSS 43 and 63," IOM 3333-75-048, Jet Propulsion Laboratory, Pasadena, Calif., Apr. 1, 1975 (an internal document). 4. Otoshi, T. Y., and Stelzried, C. T., "S/X Experiment: A New Configuration for Ground System Range Calibrations With the Zero Delay Device," in The Deep Space Network Progress Report 42-20, pp. 57-63, Jet Propulsion Laboratory, Pasadena, Calif., Apr. 15, 1974. 24 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 References (contd) 5. Christensen, C., "Corrected Mariner 10 Range Residuals," IOM 391.8-268, Jet Propulsion Laboratory, Pasadena, Calif., Apr. 24, 1975 (an internal document). 6. Otoshi, T. Y., "S/X Band Experiment: A Study of the Effects of Multipath on Tvvo-Way Range," in The Deep Space Network Progress Report 42-25, pp. 69-83, Jet Propulsion Laboratory, Pasadena, Calif., Feb. 15, 1975. 7. Ludvvig, A. C., "Multipath Calculations for Range Error Calibration Probe," IOM 3333-75-161, Jet Propulsion Laboratory, Pasadena, Calif., Aug. 22, 1975 (an internal document). 8. Bathker, D. B., Predicted and Measured Power Density Description of a Large Ground Microwave System, Technical Memorandum 33-433, Jet Propulsion Laboratory, Pasadena, Calif., Apr. 15,1971. See Eta S Column in Table II, p. 31. 9. Katow, M. S., "64-m Subreflector-Gravity Deflections," IOM 3324-75-136, Jet Propulsion Laboratory, Pasadena, Calif., Sept. 2, 1975 (an internal document). Acknowledgments The author would like to acknowledge the assistance of J. LuValle of Network Operations in writing the test procedure for overseas station tests. Splendid cooperation was obtained from G. Pasero of DSS 63 and R. Denize of DSS 43, who took the data and furnished additional details about the test configurations. H. Marks of Informatics wrote the Engineering Calibration Program used in the tests and has made the program tapes and documentation available to all stations in the Network. T. Cullen of the Communications Elements Research Section wrote the sophisticated computer program that enabled the theoretical portion of this work to be successful. The subreflector technique was originally suggested by Dr. R. W. Beatty, Consulting Electronics Engineer, for purposes of checking ranging system measurement accuracy. His suggested subreflector tests subsequently led to the discovery of the multipath phenomenon. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 25 Table 1. Multipath test configuration and tabulation of critical multipath-dependent parameters Test frequencies, Normal subreflector ' L cu _, DSS GHz operating position, Z.DD hom S'band — . luoalioii uone Uplink Downlink m' Dish surface 43 2.115770 2.297670 0 as indicated SPD on Fig. 8 Dish surface 63 2.115700 2.297593 , 7 v as indicated SPD(0.5 in. IN) on Fig. 8 Bo* on side of Mod III 14 2.115650 2.297540 (o.S^IN) slnTeTeve" as SPD cone platform (Fig. 8) S/X dichroic Approximate period plate for which test installed results are valid August 1, 1974 ( new horn location ) M t0No February 13, 1975 ( when XROa cone and S/X feed installed ) Throughout 1974 to No February 1975 ( when S/X feed installed ) March 19, 1975 when SPDb cone/ Yes XRO cone installed) to present aX-band receive only. bS-band polarization diversity. 26 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 5 l/> i|0 *.ENGTHS(LEAKAGI xjE°~ i—IIo *; x -; ? -o - s 2 £ z 7 S f|s 5 X » ^ O ^ §< S " ZQz< §O o N IJ CD•^^ _ o 5<6 < O -i 2 z o iy O S Ju £ u _< ^ > O " x 1/1 ^ I oO 1 - °5 n U . < O O2S<3 x U / ^ ^ - f ^ — i f z o ' U J C D O U g u . 0 ^ > ° 0 ™ x X => 5¥ "S5 •i ^ 13 a . o* - £> o o JPL DEEP SPACE NETW ORK PROGRESS REPORT 42-29 27 oss »j SUBRFFL TESTS AT ZENITH. 197* S»T on MS FAS 2.115770 «HZ tB- 2.297670 8HZ AOBLZ-2«.OOflO M AOBU3-15.0000 08 OLZLS 1295.000 INCH DLZIG IMS. 000 INCH SUBREF POSITION (INCH) -9.000 -z.soo -2.000 -1.500 -1.000 -.500 .000 .500 1.000 1.500 2.000 BEST FIT FIRST ES EXPCR. CALC. RAN6E RAN«E DELAY OELAT (MS) (N$> 3226. SO 3223.15 3227.90 3227.77 3202.20 3203.23 3162.60 316*. 89 3171.20 317*. *0 3210.80 3211.96 3227.20 3226.98 3210. *0 3212.25 3181. *9 3178.36 3176.60 3172.69 3195.90 3196.9* VALUES FOR OPTION Kl (NSI FIXATE 3198,51 FINAL ESTIMATE 319*,*! RAN8E OIFF. INS) 3.6*6 .126 -1.028 -2.286 -3.203 -1.16* .220 -1.8*5 3.0*0 5.9S* -l.»*0 1 Aoe -15. »5 -15.38 *xp A8C(MM) -121.1* -120.00 -122.3* -125.59 -125.22 -121.98 -119.87 -121.07 -124.05 -12*. 55 -122.81 OLZ IINCHI 1311.900 1311. *86 CALC ASC (08*11 -120.72 -120.25 -122. »7 -125.20 -12*. 55 -121.70 -120.39 -121.66 -12*. 21 -12*. 70 -122.79 K2 <08«> -122.6793 A«C nlFF. (OB) -.*21 .252 .139 -.385 -.668 -.272 .»81 .586 .169 .159 -.026 3230' 3220 3210 > 3200 UJ O UJ 8 3190 3180 3170 3160 -119 CALCULATED VALUE OF TRUE RANGE DELAY Fig. 2. Sample printout of computer program for DSS 43 subreflector tests OPERATING POINT AT ZENITH CALCULATED VALUE OF TRUE SIGNAL LEVEL-, -126 -2 -1 0 SUBREFLECTOI POSITION, in. ORIGINAL PAGE IS OF POOR QUALITY Fig, 3. Comparison of theoretical and experimental results for subreflector tests at DSS 43 on 1974 GMT Day 362 (zenith mea- surement): (a) Range delay, (b) Downlink received signal level 28 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 OSS 63 U/bREFL ICSTS AT iENlTHt 1975 ttMT DAT 29 ft* 2.115700 GhZ FB= 1.29759) CHZ Aoek*-2o.oooo Ob ADdu=-i2.ooou oa M.ZLS 1295.000 INCH OLZliS 1Mb. 000 INCH SMMEF KOSIMO* (INCH) -4.000 -K.500 -2.000 -I. SOU -1.000 -.SOU • 000 .500 l.ouu 1.50U tt.OOU 2.50U 3.00V BCSI Fll FIRVT til EXPER. C*LC. RANbC RANK OCkAV 0£L»T (NS) INS) «217.20 «198.»S »25a.»0 4255.99 •2SJ.IO «263.*2 »219.40 *235.*1 4122.60 «1)1.17 «155.90 M59.18 »2SJ.iO *2«5.2) H276.90 4260.77 H256.10 *250.9} 0201.10 »»76.0H «122.*0 0121. *7 0201.70 0223.11 0259.60 0261.05 VALUES FOR OPTION M INS) INATC 0215.10 FINAL tillXATi 0210.83 RANK OIFF. INS) 10.706 2.015 -10. SIT -22.106 -11.572 -3.27« 6.070 li.128 5.169 2J.060 .5)0 -21.006 -1.006 1 A OB (D6> -12. OU -9.70 EXP A«C ICBMI -127.07 -127.27 -127.27 -127.10 -128.25 -128.16 -127.33 -127.27 -127.27 -127.67 -126.69 -127.71 -127.28 OLZ (ISCHI 1299.500 1299.573 CALC A«C(08*) -129.60 -120.21 -123.17 -126.62 -133.0} -132.16 -125.58 -122.99 -120.90 -131.02 -133.90 -127.68 -123.86 K2 (OBH> -127.8606 AGC OIFF. (061 2.173 -3.057 -0.105 -.677 5.186 0.020 -1.7«8 -0.275 -2.373 3.352 5.2*7 -.026 -3.718 I Fig. 4. Sample printout of computer program for DSS 63 subref lector tests o *rt U CALCULATED VALUE OF TRUE RANGE DELAY CALCULATED VALUE OF TRUE SIGNAL LEVEL -130 -132 - -134 - -136 -1 0 1 SUBREFLECTOR POSITION, In. Fig. 5. Comparison of theoretical arVd experimental results for subreflector tests at DSS 63 on 1975 GMT Day 29 (zenith mea- surement): (a) Range delay, (b) Downlink received signal level JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 29 3310 HELIOs PASS 215 POST CAL OSS 1*> 1979 ONT 1AY FAS 2.1196 (N$) -3.000 3276.20 3272.7* -2.900 3253.90 3261.3* -2.000 3286.10 3289. S3 -1.500 3V>*. SO 3305.28 -1.000 3305.30 1304.02 -.900 3279.60 3282.72 .000 3266.50 3263.51 .500 3276.60 3275.99 1.000 3295.00 3298.83 1.500 3306.70 3305.02 2.000 3289.00 3290.37 2.500 3266.60 3270.71 3.000 3278.70 3271.8* BEST FIT VALUES FOR OPTION Kl (NS> FIRST ESTIMATE 3286.38 FINAL ESTIMATE 3286.4* RAN8C DIFF. (NS> 3.465 -5.442 .57* -.983 1.279 -3.118 2.999 .60S -3.83* 1.685 -1.370 -4.107 6.896 1 ADB (OB) -19.09 -19.19 > INCH rxp A8C (MM) -135.6* -136.50 -134.68 -132. »0 -132.73 -134.88 -136.1* -135.32 -133.22 -132.75 -IS*. 71 -136.36 -135.35 •H.Z (INCH) 1308.500 1308.580 193 CALC A8C (DB*» -135.57 -136.1* -134.61 -13*.«3 -133.05 -134.81 -136.19 -135.29 -133.50 -132.97 -134.17 -135.67 -135.59 K2 (00**) -1M.451. A6C (net -.070 -.163 -.066 .532 .31* -.07t .051 -.02« .277 .217 -.5*8 -.687 .236 Fig. 6. Sample printout of computer program for OSS 14 subref lector tests CALCULATED VALUE OF TRUE RANGE DELAY CALCULATED VALUE OF TRUE SIGNAL LEVEL -136.5 -2 -\ 0 I SUBREFLECTOR POSITION, in. Fig. 7. Comparison of theoretical and experimental results for subreflector tests at DSS 14 on 1975 GMT Day 193 (zenith mea- surement): (a) Range delay, (b) Downlink received signal level 30 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 DSS43 ZDD LOCATION ON DISH SURFACE (640 cm FROM PARABOLOID CENTER) AFTER 1974 GMT DAY 213 BAY 3 NO CONE (XRO CONE INSTALLED AFTER FEB. 197S) EDGE Of DISH LOCATION OF ZDD PRIOR TO 1774 GMT DAY 213 BAY 2 SPD CONE (NO ELLIPSOD) GROUND DSS63 BAY 3 XRO CONE (NO DCHROC PLATE) ZDD ON D6H SURFACE (648 cm FROM PARABOLOID CENTER BAY 2 SPD CONE (NO ELLIPSOD) GROUND BAY 3 XRO CONE (FIXED DICHROIC PLATE) - DSS 14 QUADS IPOD LEG BAY 2 SPD CONE (FIXED ELLIPSOID) NOT TO SCALE BAY 1 XKR CONE (NO DICHROIC PLATE) ZDD LOCATED IN BOX ON SAME LEVEL AS CONE PLATFORM ONSDEOFMODTJI SECTION GROUND Fig. 8. DSS 43, DSS 63, and DSS 14 zero-delay device locations and tricone configuration for subreflector tests JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 31 Zu > -10 UJ O UJ OI -15 -20 -25 -120.0 -120.5 I -121.0 _l UJ 3 J -121.5 Z O ^ -122.0 -122.5 -123.0 (o) ZENITH - O i i • 4H.-ORDER POLYNOMIAL CURVE FIT RANGE DELAY CHANGE - (RANGE AT ELEVATION ANGLE) -(RANGE AT ZENITH) - 6th-ORDER POLYNOMIAL CURVE FIT 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 ELEVATION ANGLE, deg 50 40 0 a IU O i 20 10 -10 -127.30 -127.35 4-127.40 (a) ' M -ORDER POLYNOMIAL CURVE FIT RANGE DELAY CHANGE • (RANGE AT ELEVATION ANGLE) - (RANGE AT ZENITH) i i i i Z a -127.45 -127.50 T-127.55 -127.40 I I I 1 1 I I i 7th -ORDER POLYNOMIAL CURVE FIT 10 20 30 40 50 60 70 ELEVATION ANGLE, deg 80 90 rig. 9. DSS 43 antenna tipping tests at S-band, 1974 GMT Day 359: (a) Range delay change, (b) Downlink received signal level Fig. 10. DSS 63 antenna tipping tests at S-band, 1975 GMT Day 27: (a) Range delay change, (b) Downlink received signal level 32 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 N76 14301 Calculating Acquisition Behavior for Completely Digital Phase-Locked Loops J. R. Lesh Communications Systems Research Section The acquisition behavior of completely digital first and second-order phase- locked loops is considered. It is shown that modeling the loop by its difference equations allows the acquisition behavior to be computed using a procedure wherein the number of computations as well as the required storage grow only linearly with the size of the state space. It is also shown that the procedure can be easily modified to include the effects of doppler, finite length accumulators, and initial phase estimate jamming. I. Introduction At present very little is known analytically about the acquisition behavior of phase-locked loops. The primary reason for this is that the linearizing or simplifying as- sumptions used in calculating steady-state performance parameters are not applicable when, the loop is in the acquisition mode. However, if one considers completely digital phase-locked loops (Refs. 1, 2), then any imple- mentation of such a loop is necessarily a finite state machine. In such cases if one is given, an initial state distribution vector, then one can, at least in principle, compute any subsequent time-state distribution vector by considering the loop as a finite state Markov chain and multiplying the initial state distribution vector by the appropriate power of the Markov transition matrix. Unfortunately the number of computations as well as the storage required for this procedure both increase as the square of the size of the state space, making such a pro- cedure quite unattractive for all but the smaller state spaces. For example, Chadwick (Ref. 3) used this tech- nique to compute the acquisition behavior of a digital tracking loop which, even after restricting himself to a most likely subset of the state space, resulted in a one- step Markov transition matrix having 6.25 X 10s entries. The important point, which seems to have been over- looked in the past, is that for tracking loops of the kind described in Refs. 1 and 2 most of the entries in the Markov transition matrix are zeros. Consequently, if one characterizes the loop by its difference equations then only the essential computations need be performed. This results in a tremendous savings both in computations and storage. In this article we will use the difference equation approach for computing acquisition performance of first- and second-order digital loops. We will see that this JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 33 approach can be easily modified to include the effects of finite accumulators (for the second-order loop) and dop- pler. Finally, we will show how this approach can be used to evaluate the merits of initial phase estimate jam- ming. II. First-Order Loop Consider the completely digital first-order phase- locked loop shown in Fig. 1. In this loop the input signal (a squarewave signal immersed in additive white gauss- ian noise) is filtered, sampled at the Nyquist rate and is applied to the transition sample selector. The transition sample selector, which is controlled by the phase shifter, extracts the sample of the input signal which is believed to have occurred at the transition of the received signal and corrects for the expected sign of this sample. The result is then accumulated until a sufficiently high signal- to-noise ratio is obtained to estimate (with high proba- bility) whether the loop reference supplied by the phase shifter is leading or lagging the received signal. If the reference is leading the received signal, the accumulator will accumulate positively whereas it will accumulate negatively if the reference is lagging. After the accumu- lation has been completed, the sign of the accumulator output is used to shift or bump the phase of the loop reference signal one step in the direction to reduce the expected phase error, and the accumulator is reset. The steady-state behavior of such a loop has been amply studied by Holmes (Ref. 1). For the acquisition behavior let us consider that the phase bump size is 2^/K radians. Then the loop can be considered as a Markov chain having K states. Let us consider (without loss of generality) that the phase of the received signal is zero. Furthermore, we will take the pessimistic approach by assuming that the phase error when the loop is in the feth state k is We now define the state probability vector K ,. radians for fc= 1, 2, for v •, — , and £i (2K -2k- I)TT ,. k = — — radiansK. (2) S((2) 8,(K) (3) where s,(k) is the probability of being in state fc at time t. Since the loop is discrete, we assume that t belongs to the index set (i.e., t e {0,1,2, • • •}). Then, from Fig. 2 and the theory of Markov chains we know that S, = [P] S0 (4) where s0 is the initial state distribution vector and P is the K by K one-step Markov transition matrix given by 0 p q 0 p q 0 p K q 0 p q o q q 0 q p 0 q (5) A state diagram for this loop is shown in Fig. 2. p 0 q p 0 In this equation p is the probability that the accumula- tion will cause a phase bump in the direction to decrease the phase error, q = 1 — p, and the blanks are assumed to be filled with zeros. In order to compute the state probability distribution after one accumulation using this procedure we must store (aside from the distribution vectors themselves) a matrix having K2 entries and perform K2 computations. However, if one characterizes the loop by its stochastic difference equations, a tremendous savings in both stor- 34 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 age and computations is achieved. In particular we note that the loop can be characterized by ps,(k + l )+ps,(k-l + K); k=l pst (k + 1) + qst (k - 1); it £ [2, K/2 - 1] qs t (k+l ) + qs,(k- 1); k = K/2,K/2+l (6) ps, (k + l -K) + ps t(k-l); k = K By using this characterization the one-step probability distribution vector can be computed with only 2K computations and with a storage only slightly greater than that required to store the probability vectors themselves. variable is fixed at some value. Note, however, that for the second-order loop no transitions within a given ring are allowed (except possibly at the extremes which will be considered later) and that only certain transitions be- tween rings are allowed. One can further visualize this series of rings as forming a tube with each ring on the tube being rotated about the tube axis by an amount dependent on the location of the ring (value of x;) as well as the value of n. With this picture in mind, let us define s, (k, 1) as the probability of being in the fcth error state at time t with a loop filter value of L We can further consider a ring probability vector III. Second-Order Loop The first-order loop of Fig. 1 can be converted to a second-order loop by inserting a filter of the form shown in Fig. 3 between the accumulator sign detector and the phase shifter. The effect of this filter is to cause the phase shifter to be bumped by u "n + x2 units where u = ± 1 is the output of the accumulator sign detector, n is an integer gain factor and x? is the value (after u is added) of the loop filter accumulator. For such loops one must specify the values of two state variables in order to characterize the state of the loop. We shall use the instantaneous phase error, as we did in the first-order case, for one of these variables and the output x, of the loop filter summer as the other. It is convenient to view the state space of the second- order loop as a series of rings similar to the one shown in Fig. 2, where each ring corresponds to all possible values of instantaneous phase when the second state The loop stochastic difference equations are (assuming no restriction on i): (a) | I | n ps, (fc + 1 + n,l - l )+qs t (k + t-n,l + l); kJ 1, y - n - 11 - n - n - n - - n - (8c) ps,(fc + l + n,l-l) + ps,(fc + l-n,l + 1); k e [ K - n - l + l,K + n-l] pst (k + i + n - K, 1 - 1) + qst (k + 1 - n - K, I + 1); ke [K + n - 1 + 1, K] where it is assumed that the interval (set) [a,b] is empty if b < a. As in the first-order case, we see that the amount of storage necessary to accommodate these equations is essentially the same as the amount of storage necessary to store the state probabilities. Therefore, the storage grows linearly with the range of 1 (=x2). Note also that the number of computations grows linearly with the size of the state space. IV. Practical Considerations (a) Accumulator Truncation In any implementation of a discrete second-order phase-locked loop, the accumulator in the loop filter will have a finite range. For example, we will let x«e [Lmio, LmaJ- This is equivalent to placing saturating boundaries at the L^ and Lmin rings of the tubular state space. Any attempt to penetrate beyond the LmaJt(Lmln) ring results in a transition back onto a state in the Lmal(Lmin) ring. The difference equations of the second-order loop can be easily modified to accommodate this saturation of the state space. First, we note that each of the expressions in Eq. (8) is of the form a, + , (M) = o», (*M - 1) + PS, (k",i + 1) over the appropriate range of k. If i is one of the satu- rating boundaries, then one of the two rings (i + 1) or (1 — 1) does not exist. In fact, the only way to get to the 1th ring is to either be on the interior ring next to 1 or to be on the 1th ring already. As a consequence, we see that if 1 = Lmax then we can add the set of equations = as, as, (9) over the appropriate range of k and where the quantities a and k' are determined by the range of i in equation 8 36 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 corresponding to i = we add the equations Similarly, if £ = Lmln then If we denote (10) again over the appropriate ranges of k. Thus, the Eqs. (8) apply to all interior rings and one need only add the set.of modified equations for each boundary ring. (b) Doppler The effects of doppler can be quite easily handled pro- vided one is willing to use a finite-state approximation approach. For example, if a loop has K phase error states and phase bumps every tup seconds then one can approx- imate a doppler offset of D/Ktav Hz (D an integer) by cyclically shifting each ring probability vector by D positions after each phase bump interval. If D is not an integer then one can either bound the desired result by using the appropriate neighboring integer or can further approximate by periodically selecting the amount of cyclic shift from a set of neighboring integers. V. Initial Phase Estimate Jamming Let us now assume that the received signal where s(t,£) = Asgn [sin[wt + '[_ 16'ieJ (11) and is uniformly distributed in this interval. Assume also that s(t,£) is to be correlated over the interval {- MT MT2 ' 2 with each of the reference signals *i(0 = sSn (sin[wt -i where -j (12) /• I/*T ,[- I -M*T J o (13) and perform the integration, we obtain i=-7,-8,-",6,7 ori = 8and|>0 (-A,MT(l-l = 8and£<0 (14) We note that if Af = A Eq. (14) does not include the effects of doppler. To include doppler, one need only replace Aj by a gx) Pr {ga > g.,} (19) as well as Pr {gi = maxg,} < Pr {gs > go} (20) Finally, we note that 225Pr {g8=maxgy}l (21) where | is the estimated phase. Substituting (19) and (20) into (21) yields the final bound. VI. Examples (a) First-Order Loop The acquisition performance of a first-order loop hav- ing 256 states is shown in Figs. 4 and 5. It is assumed that the loop is updated (bumped) every M cycles of the received signal and that the initial phase estimation is based on an observation of the signal for M* = NM cycles. For N = 0 (i.e.,' no initial estimation), the initial state distribution vector is uniform. For N > 0, the mean square phase error due to phase estimation is first com- puted using the results of Section V. The initial state distribution is then taken as a quantized gaussian distri- bution with zero mean and this mean square error as a variance. The time axes have been normalized by the time required for M cycles (t,,p). Figure 4 represents the acquisition behavior when the loop update SNR MTA* _ and when no doppler is present. Figure 5 illustrates the behavior under the same conditions, except that a dop- pler offset was simulated by cycling the state probability vector one position every two updates. (b) Second-Order Loop Figures 6 to 8 demonstrate the acquisition behavior of a second-order loop similiar to the one described in Ref. 4. Here the phase variable has 256 discrete values and the proportional control gain factor n = 4. The range of the second state variable x2 was restricted to the inter- val [—3, 4], Figure 6 shows the acquisition with no doppler. Figures 7 and 8 illustrate the acquisition be- havior when the numbers of doppler-generated shifts per loop update are 2 and 4, respectively. (c) Discussion By examination of Figs. 4 to 8, we see that if one is interested in fast acquisition then a large portion of the acquisition time should be allocated to phase estimate jamming. This is particularly true for the first-order loop, since the closed-loop time constant is generally quite large. For the second-order loop much less is to be gained by jamming unless the doppler offset is quite large. Note, however, that the doppler cannot be allowed to increase indefinitely since, as is shown in the appendix, if the estimator integration time equals the time needed to accumulate one complete doppler shifted cycle, the received signal will be orthogonal to all estimator refer- ence signals. VII. Summary Described herein is a procedure for computing acqui- sition performance of first- and second-order digital loops which requires only a linear increase in storage and computations with the size of the state space. The pro- cedure was found to be easily modified to account for finite accumulators and doppler. Expressions for the initial state mean square error after phase jam estimation were developed and several examples were presented to show the relative merits of phase jamming as an initial part of acquisition. 38 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 FROM ACCUMULATOR SIGN DETECTOR TO PHASE SHIFTER Fig. 1. First-order phase-locked loop block diagram Fig. 3. Second-order digital PLL loop filter -- i K -1 30 O' 20 10 N = 0 20 40 60 80 100 Fig. 2. Representation of state space for first-order PLL Fig. 4. Acquisition performance of first-order digital loop (no doppler) Jf»L DEEP SPACE NETWORK PROGRESS REPORT 42-29 39 30 20 i 10 20 40 60 'A. 80 100 Fig. 5. Acquisition performance of first-order digital loop (one doppler state shift every two updates) Fig. 6. Acquisition performance of second-order loop (no doppler) 40 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 50 40 30 § LU UJ i/) 2 20 10 IN = o 10 2 SHIFTS/UPDATE 20 'Aup 30 40 Fig. 7. Acquisition performance of second-order loop (2 doppler shifts per update) i 50 40 30 20 10 4 SHIFTS/UPDATE 10 20 UP 30 40 Fig. 8. Acquisition performance of second-order loop (4 doppler shifts per update) JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 41 Appendix Signal Correlation in the Presence of Doppler Consider a reference signal s(t) of the form > s(t) = sgn{sin[W0(t-0)]} and a received signal of the form «"(*).= A sgn {sin [W^f- Let the two signals be correlated for a time interval of M*T seconds where T — ZTT/WO and M* is an even integer. The correlator output at the end of this interval will be CkC't sin[~(fcW0 + iWO-^pl «(*X(*)* = 2 ,.2.. .2,. irw ^ ,w J 00 00 I__M»T ./ —— where 2exp( —;fcW00) ; fc odd 0 ; k even and ' 2Aexp(-/fcW1g>) 0 ; fceven Substituting the C's into (A-l) and defining gives • K»r • = -32A V V ., .?T^"'" "' i [fcW0cos (feW0(9)cos (IWJ) + iWisin(fcW0(9) sin ~^ ~—* KWTT* Jr*Vvr — V*Vvr I - * 2wn ^ 2 k odd 1 odd (A-2) Now let us assume that 9' is uniformly distributed and define for T' = 2ir/Wi the intervals Furthermore, assume that if 42 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 then for /« {0,1, • • • ,15}. Note that for S small, then T'=* T and 0 corresponds to the midpoint of one of the 16 intervals A'f. Next, define Bt(J,S,M') as the average over 0'eA'i when 6 is given by (A-3). Performing this average yields * odd 1 odd (A-4) It is our intent to average (A-4) over the 16 values of i. However, in most practical systems some band limiting exists, and hence the use of equations which display unlimited harmonic content is quite unnecessary. Therefore, we will restrict equation (A-4) to summations up to the seventh harmonic. Then, averaging over i we get sin cos S(8 - k)]M' * odd However, if 8 is small, the second term dominates the equation so that BOUT) = AMT 7 k odd - B(/,A) (A-5) where Equation (A-5) represents the average signal correlation of a reference signal and a signal which is uniformly dis- tributed in an interval / sixteenths of a period away from the reference. Finally, we note that if the doppler goes to zero then B(/,A = 0) = t = i A: odd The ratio B(/,A = 0) can be considered as the effective signal reduction factor due- to doppler. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 43 Figure A.I illustrates the behavior of |B(/,x)| (after normalization) as a function of A, the number of doppler-shifted cycles contained in the signal correlation integration time. It is instructive to note that as A increases the peaks of the triangular squarewave correlation curve are suppressed more than the interior points. This causes the correlation function or S-curve to become more rounded. This rounding continues until the integration time encompasses one complete doppler-shifted cycle at which time the received signal is orthogonal to all of the reference signals. References 1. Holmes, J. K., "Performance of a First-Order Transition Sampling Digital Phase-Locked Loop Using Random-Walk Models," IEEE Trans. Comm. Vol. COM-20, No. 2, pp. 119-131, April 1972. 2. Holmes, J. K., and Tegnelia, C. R., "A Second Order All Digital Phase Locked Loop," IEEE Trans. Comm. Vol. COM-22, No. 1, pp. 62-68, January 1974. 3. Chadwick, H. D., "A Markov Chain Technique for Determining the Acquisition Behavior of a Digital Tracking Loop," ]PL Quarterly Technical Review, Vol. 1, No. 4, pp. 49-57, January 1972. 4. Lesh, J. R., "A Multiple-Rate Digital Command Detection System With Range Cleanup Capability," in The Deep Space Network Progress Report 42-26, pp. 91-101, April 15, 1975. 44 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 1.00 0.2 0.4 0.6 0.8 1.0 Fig. Al. Signal correlation loss due to doppler JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 45 N76 14302 The Effect of Noise and Diversity on Synthetic Array Radar Imagery S. Butman and R. G. Lipes Communications Systems Research Section This article investigates synthetic aperture radar (SAR) image quality as a func- tion of received signal-to-noise ratio, multiple looks or diversity averaging of "speckle," contrast, and resolution. Theoretical and simulation results are pre- sented. The data are useful for tradeoff analyses in the design of the SAR, the image processing system, and the telemetry system. Photographs have been made to show the effect of the above-mentioned parameters. The general conclusion is that diversity averaging produces an image far superior to that obtained via equivalent receiver signal-to-noise improvement. I. Introduction One aspect of the DSN Advanced Systems Program is investigation of the flight-ground-mission control inter- faces. This has the salutary feature of resource savings to NASA through optimum (in the sense of multimission support cost) flight and ground system design. A good example is the standard command detector breadboard development. Other tradeoff areas are also being ex- amined including, in the near term, operational problems, and in the longer term, a look at likely flight projects which will require higher link performance and instru- mentation. A Venus-Orbiting Imaging Radar (VOIR) mapper has been proposed for the 1980's. The likelihood for such a mission is high, particularly since a similar Earth-orbiting mission, Sea Satellite (SEASAT), has been approved. When a VOIR-type mission is approved it will require a link capability up to 20 dB better than the current Mariner Jupiter-Saturn spacecraft/64-m antenna combi- nation can provide at X-band. Furthermore, once such a high rate link (5-25 megabits/s) comes into being, it will be necessary to equip the Network with appropriate instrumentation to receive, detect, decode, and handle these data. These science data can be anticipated to be essentially raw radar echoes received on the spacecraft and telemetered to Earth, either in real-time or after tem- porary storage on board. These raw data will require processing into an image either at a DSN station or at the mission communication and control center, depending on processing cost vs ground communication cost. In either case, the DSN will need a capability to meet certain performance criteria pertaining to data quality (in this case, synthetic array radar image quality). 46 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 The purpose of this paper is to report some progress on the relationship between image quality, signal-to-noise ratio, and processing techniques. This type of informa- tion is expected, ultimately, to influence the design of the spacecraft and the ground system. Here we will be dis- cussing picture formation via synthetic array radar signal processing. Pictures obtained in this manner exhibit "speckle" or self-noise, which can be removed through the introduction of diversity. We first give a brief theoretical discussion of the underlying causes of speckle and its removal, followed by a discussion of simulation results and conclusions on this phase of the study. II. Speckle When monochromatic coherent radiation is scattered off a surface, the return is a coherent superposition of contributions from the elementary scattering centers of the surface. When the roughness or height variation of the surface is approximately equal to or greater than the wavelength of the radiation,1 the phases of the contribu- tions from the elementary scattering centers can be closely approximated as independent random variables uniformly distributed between 0 and 2w. When the number of scattering centers is sufficiently large so that the central limit theorem can be applied to the super- position of elementary contributions, the amplitude of the return signal can be closely approximated as a Rayleigh distributed random variable.2 The power s of the return will be exponentially distributed, having the probability density function ?(*)=«"/« I (1) where S is the mean power of the return. This phenom- enon has recently been called "speckle" by the workers in optics (Refs. 2-4), although it has been noted by the 'This admittedly crude definition of a "rough" surface is qualita- tively the Rayleigh criterion, which states that a surface is rough or smooth depending on whether the height variation at grazing angle is respectively greater than or less than X/8 sin y, X being the wavelength of the radiation. For a discussion of the validity of the Rayleigh criterion, see Ref. 1. 2The theoretical hypotheses under which the amplitude will be Rayleigh-distributed are enumerated in Ref. 1, Chapter 7. Pub- lished data that verify the validity of these hypotheses are sur- prisingly rare; in fact, we have been unable to find any data of terrestrial radar returns that directly exhibit a Rayleigh amplitude distribution. Reference 1, page 463, presents evidence for the lunar radar return with a Rayleigh-distributed amplitude. Refer- ence 5, pages 515-518, gives experimental evidence of Rayleigh- distributed amplitudes in radar returns from the sea. workers in radar (Ref. 5) and certainly dates back to Lord Rayleigh (Ref. 6). In many cases we want to obtain information about the features of the illuminated surface from the rehim signal. However, the features of a certain area are related to the mean power S of the return from this area, while the actual power s of the return is probabilistic. For this reason we need to employ some form of diversity recep- tion to obtain the average power. Typically, this diversity takes the form of space diversity, which means that the surface is observed from independent vantage points and the results of the independent "multiple looks" are aver- aged. Another common form is frequency diversity, in which results from independent looks with radiation of different frequencies are averaged. Whatever the form, the results from multiple looks must be added incoher- ently to approximate the average power return from the surface. III. Speckle Reduction via Multiple Looks In this study we wanted to simulate the effects of the "speckle" phenomenon as it would apply to a picture processed from satellite radar data. We chose an Earth Resources Technology Satellite (ERTS) optical picture that was put on magnetic tape with picture elements (pixels) representing 57- X 79-m resolution cells. The picture shown in Fig. 1 (low contrast original) represents the ERTS data from an area approximately 15.4 km left- right by 21.3 km up-down (270 X 270 pixels). Each pixel is quantized to 6 bits on the tape, representing 1 of 64 shades between black and white. To simulate the radar "speckle" we replaced each pixel value with a random variable exponentially distributed according to Eq. (1), with the mean value S taken as the original pixel value. This resulted in the picture (low contrast, 1 look) shown in the lower center of Fig. 1. As one can see, the image content is almost entirely lost. This photograph represents an extreme effect that the radar speckle would have on a single "look." We then repeated this procedure 4, 16, and 64 times, and averaged the independent results to generate the pic- tures (low contrast series) shown in the center region of Fig. 1. Mathematically, we generated N identically dis- tributed random variables, s,,' • ',sa and computed and plotted A/ = 1,4,16,64 for each pixel. Here, Af represents the number of "looks." JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 47 The mean of Sj, is still S, but the variance "I = (SM~S)- = --- (2) is reduced by the factor 1/M compared to a single look. Therefore, the signal-to-noise ratio (SNR) per pixel as defined by ratio of power in signal to standard deviation of that power SNRpixel = — = (3) increases 3 dB per 4-fold increase in Af. From these photographs we see that a reasonable facsimile of the original picture is obtained for some number of looks between 16 and 64. The original Earth Resources Technology Satellite (ERTS) picture and the pictures simulating the multiple looks are all of a scene with rather low contrast. Figure 2 shows a histogram of the original pixels in the scene. The ordinate is the number of pixels n, having a giyen value S (between 0 and 63), and the abscissa is the value S. Even though 64 contrast levels are available, these pictures are effectively using only about 10 levels. To increase con- trast in the developed original image we uniformly "stretched" the pixel values to cover the full dynamic range of 64 levels by rescaling the data on the tape. This .was accomplished for each pixel by the mapping. S -> S' = 13(S - 10)/3 (4) where S' is the new pixel value given the cell that orig- inally had pixel value S. (Of course, new pixel values less than 0 or greater than 63 were set to 0 and 63, respec- tively.) The high-contrast ERTS picture now has the histogram shown in Fig. 3. This higher-contrast original was once again studied for the effects of speckle. The resulting ERTS picture and those simulating 1, 4, 16, and 64 looks (high contrast series) are shown in the left- hand column of Fig. 1. Higher original contrast con- siderably improves the speckled image. In fact, the 16-look simulation reveals most of the features of the original high-contrast ERTS picture. IV. Resolution vs Multiple-Look Tradeoff Next, we studied the procedure of sacrificing resolu- tion to increase the effective number of looks. This was accomplished by averaging returns from adjacent resolu- tion cells. We took the multiple-look pictures of the center column of Fig. 1 (low contrast series) and replaced the pixel values of 4 adjacent pixels (2 up-down and 2 left-right) by the average of the 4. This procedure is illus- trated in Fig; 4. Notice that the effective resolution cell area has increased by a factor of 4 as the result of this averaging, so we have sacrificed resolution to obtain more looks. Since we have increased the effective number of looks by a factor of 4, the information content of the low- resolution A/ look system should be close to that of the original 4Af-look system. The problem in making a visual comparison is that the resolution limit of the original sys- tem is determined by the area of a single pixel, while for the low-resolution system, it is determined by the area of 4 adjacent pixels. To facilitate this comparison we have decreased the area of the low-resolution series by a factor of 4. In Fig. 1 we see the resolution vs multiple-look tradeoff by comparing the center and right-hand columns. The information content of low-resolution Af-look system is greater than that of the original Af-look system and approaches but does not reach that of the original 4Af- look system for M = 1, 4, and 16. V. Effect of Additive Noise To investigate the effects of receiver and downlink noise on picture quality, we introduced varying amounts of additive white Gaussian noise (AWGN) to the multi- look pictures. Since each pixel is formed by envelope- detecting an in-phase and a quadrature signal, which are themselves contaminated by receiver noise, the situation is described by vt = (5) where a,,a^ are the in-phase and quadrature voltages in the pixel from the scene in the absence of noise, and n,,nQ are the corresponding contaminating voltages in the pixel due to noise. The signal power s, noise power n, and total power v in the pixel are given by s = a,2 + aQ* n = n,2 + nQ 2 (6) and v = These random variables are exponentially distributed since they are sums of squares of pairs of independent, identically distributed, zero mean gaussian random 48 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 variables. Moreover, since ai,aO O T JO ORIGINAL PAGE IS OF POOR QUAJJTY « ° Iff I" 0 c in c -o *ga>IDOCv>V)00 IDOil JPL DEEP SPACE NETW ORK PROGRESS REPORT 42-29 53 An X-Band Radiometer for the Microwave Weather Project M. S. Reid, 0. B. Parham, and R. A. Gardner Communications Elements Research Section A stabilized high-resolution X-band radiometer has been designed, constructed, and is presently operating at the Venus Deep Space Station in the Goldstone Deep Space Communications Complex in California. The radiometer is an automatically switched and automatically calibrated noise-adding radiometer and is used for atmospheric propagation research for the Microwave Weather Project. This re- port describes the radiometer, its sensitivity, and gives examples of its performance. I. Introduction The Microwave Weather Project forms part of an overall Radio Systems Development Project which seeks to optimize the spacecraft-to-ground communications link. The objective is to provide a mathematical model of atmospheric transmission at X- and K,,-bands. This model will allow practical predictions of link performance to be made and will also form the basis of a specification of the receiving sensitivity of a Deep Space Network ground station. The model, which contains both probabilistic and deterministic elements, is based on the statistical correlations of weather and communications capability at X- and K,,-bands. Previous reports (Refs. 1, 2) have dis- cussed the Microwave Weather Project and described the method and equipment used to build a suitable data base from which the mathematical model can be designed. They also described the difficulty of acquiring sufficient data of good quality using the existing X- and Ku-band radiometers on the 64-m antenna at DSS 14 at Goldstone DSCC. In order to improve both the quantity and quality of the X-band data, a radiometer has been designed, built, and installed at DSS 13. This radiometer is a high- precision instrument that is dedicated to the Weather Project and which operates 24 hours-per-day automati- cally collecting data. This report describes this radiometer and its method of operation. II. The Equipment Figure 1 shows a block diagram of the X-band radiom- eter. The antenna is a corrugated horn which is directly coupled to a waveguide switch. The switch can connect the receiver to the horn, an ambient termination or a liquid nitrogen-cooled termination. The horn is built to the same design as the X-band horns used in the X-band radar, transmit-receive; K-band receive (XKR) cone on the 64-m antenna at DSS 14 and the Multiple Frequency X- and K-Band (MXK) cone which preceded it on the antenna. The gain of the horn is 22.3 dB; the dissipation 54 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 loss in the horn contributes IK, +0.5, —0.25 (K) in noise temperature; the 3-dB beamwidth is 7 deg (half angle) and the gain is down 10 to 12 dB at a half angle of 15 deg. The receiver is a mixer and IF amplifier, the output of which feeds a detector which has been described in several previous reports, (Refs. 3-6). The computing counter and programmer form a noise adding radiometer (NAR), (Ref. 7), whose noise diode feeds into the re- ceiver through a coupler, as shown in the diagram. The output from the NAR feeds a data acquisition system, which is described elsewhere. The block diagram shows that two local oscillators (LO) are available, only one of which is used at a time. These two solid state LO's are set a few hundred megahertz apart, which allows ample frequency agility to avoid interference by microwave communication links or X-band transmitters. The LO presently in use is set at 8498 MHz. The noise diode and its input coupler, the receiver, the local oscillators and all the interconnecting lines between these items are all temperature controlled to ±2°C in an environmental enclosure. This is shown schematically in the diagram. In normal operation the radiometer is automatically switched between the horn and the ambient load. This is an additional calibration capability and is described in the next section. The liquid nitrogen-cooled load is not used in routine operation; it is a precision calibration tool which is used manually, approximately once per month. The waveguide system and horn are pressurized with dry nitrogen gas. The radiometer is enclosed in a suitable box, which is mounted on an elevation-over-azimuth electric antenna drive. Figures 2 and 3 are photographs of the svstem. III. Calibration by the Cryogenic Load A precision calibration using the cryogenic load is carried out manually at periodic intervals. This serves primarily to calibrate the noise temperature of the noise diode (T\) . Regular measurements of 7\ will keep a check on the noise diode aging, and thus remove the possibility of these effects (or other slow drifts) from contaminating the data quality. The calibration is carried out by adjusting the value of Tv so that the NAR output corresponds with the calibrated thermal noise tempera- ture of the cryogenic load when the receiver is connected to this load. IV. Routine Operation In routine operation the waveguide switch is auto- matically controlled by the NAR programmer to switch the receiver to the horn for one minute and then to the ambient load for one minute. This cycle is repeated con- tinuously during normal operation. With the receiver connected to the ambient load the NAR measures a system operating noise temperature in kelvins (T1,,,,), such that np load (1) where Tf: = receiver front-end excess noise temperature (K) TV = physical temperature of the ambient load (K). The reference plane for TV is the input to the waveguide switch. TV is measured by a quartz thermometer in the ambient load and therefore the programmer can solve for TV. The value for TE is calculated every second minute when the receiver is connected to the ambient load. When the receiver is connected to the horn the NAR measures a system operating noise temperature (Top|horn) such that T'op hum — Ta,mnl, + Tt: + Tf + I II (2) where Tan,,,,, = noise temperature due to the atmosphere (K) T, = cosmic background temperature (K) TH = noise temperature due to horn losses and a waveguide component, consisting of a stepped transition from circular to rectangular guide and about 3 cm in length, and any possible mismatches (K) The values for T, and T,, are assumed constant, 7Y+ TV, =2.7+ 1.7 = 4.4 K (3) TV. has been automatically measured and calculated by the NAR from Eq. (1) and therefore the NAR computes the noise temperature due to the atmosphere by T«tmo« = Top horn — (TV + TC + TH) (4) JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 55 On a clear day with the horn at zenith the atmospheric noise temperature is usually about 2.6 K. V. Radiometer Sensitivity The sensitivity of the NAR has been shown (Ref. 7) to be: 2TOP(1 A Tm i n = kelvins (5) where B = detector bandwidth, Hz T = equivalent integration time of the output integra- tor, sec The bandwidth of the system is presently set at 20 MHz (10-MHz double sideband centered at 8448 and 8548 MHz). Top, with the receiver connected to the horn, is approximately 600 K, and with the receiver connected to the ambient load, rop is approximately 900 K. In either position the NAR switches the noise diode on and off 130 times in 52 sec. Thus 130 Top measurements are calculated and averaged every minute. The equivalent integration time is therefore 52 sec. The NAR measures TP both before and after each set of 130 Y-factor measurements on the ambient load. These two Tr measurements are averaged and used in the calculation for TE. Tv is pres- ently set to 1300 K. With these parameters the system sensitivity becomes (from Eq. (5)): =0.09K AT111Inihorn = so that the combined sensitivity (or resolution for relative atmospheric measurements, A T m i n j a , m o s ) is 0.1 K. Figure 4 shows two elevation profiles made at DSS 13 on Aug. 4, 1975 with the horn tipping to the South (azimuth 180 deg). Atmospheric noise temperature in kelvins is plotted against elevation angle in degrees. The solid data points were made at 10:00 a.m. PST in clear sky; the open data points were made at 3:00 p.m. PST with some thin clouds to the south. VI. Conclusions A stable radiometer with high resolution has been constructed at X-band for the Weather Project. It is presently operating 24 hours per day at DSS 13. The addition of a similar K,,-band radiometer is under investi- gation. 56 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 References 1. Reid, M. S., "A Description of the Weather Project," Technical Report 32-1526, Vol. X, pp. 116-122, Jet Propulsion Laboratory, Pasadena, Calif., August 15, 1972. 2. Reid, M. S., Booth, R. W. D., "Preliminary Analysis of the Microwave Weather Project Data for CY 1971," Technical Report 32-1526, Vol. XI, pp. 111-120, Jet Propulsion Laboratory, Pasadena, Calif., October 15, 1972. 3. Reid, M. S., Gardner, R. A., Stelzried, C. T., "A New Broadband Square Law Detector," Technical Report 32-1526, Vol. XVI, pp. 78-86, Jet Propulsion Laboratory, Pasadena, Calif., August 15,1973. 4. Reid, M. S., Gardner, R. A., Stelzried, C. T., "Improvement in the Accuracy of the New Broadband Square Law Detector," Technical Report 32-1526, Vol. XVIII, pp. 94-98, Jet Propulsion Laboratory, Pasadena, Calif., December 15, 1973. 5. Gardner, R. A., Stelzried, C. T., Reid, M. S., "Radiometric Applications of the New Broadband Square Law Detector," Technical Report 32-1526, Vol. XIX, pp. 89-92, Jet Propulsion Laboratory, Pasadena, Calif., February 15, 1974. 6. Reid, M. S., Gardner, R. A., Stelzried, C. T., "A New Broadband Square Law Detector," Technical Report 32-1599 (to be published). 7. Batelaan, P. D., Goldstein, R. M., Stelzried, C. T., "A Noise Adding Radiometer for use in the DSN," Space Programs Summary 37-65, Vol. 2, pp. 66-69, Jet Propulsion Laboratory, Pasadena, Calif. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 57 AMBIENT LOAD rfi LIQUID NITROGEN COOLED FT- LOCAL OSCILLATORS ^ ^ LOAD n r-^- MIXER AND IF AMPLIFIER TEMPERATURE CONTROLS 1 1 l_ DETECTOR n [_ 1 DATA ACQUISITION NOISE DIODE LIZ J STRIP CHART RECORDER PHYSICAL TEMPERATURE / FROM LOAD I COMPUTING COUNTER PROGRAMMER Fig. 1. Block diagram of the X-band radiometer DATA COUPLER 58 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Fig. 2. Photograph of the X-band radiometer Fig. 3. Photograph of the X-band radiometer * LLJ t— LU 1— LU co O z y a: UJ 1 1— 85 80 70 60 50 40 30 20 10 0 1 I I -0 • CLEAR SKY 0 SOME COUDS - - - O • - « • • ,I I I I I I 1 1 1 0 10 20 30 40 50 60 70 80 90 100 ELEVATION ANGLE, deg Fig. 4. Elevation profile of atmospheric noise temperature JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 59 14304 Aerodynamic Static Differential Pressure Values for the 50 Percent Porous Reflector Dish M. S. Katow DSN Engineering Section Although the solid and the 25 percent porous thin paraboloidal dishes were instrumented with static pressure tubes and tested in the wind tunnel, the porosity used for the 64-m antenna was 50 percent for economic reasons. The extrapolation to 50 percent porosity, to date, has resulted in conservative values. This report describes a method of extrapolating from the available data the 50 percent porous pressure coefficient differences. The method is verified by checking the available wind tunnel static pressure data against the force data. I. Introduction A series of antenna models were tested in a wind tunnel (Refs. 1 and 2) to provide wind loading data for the design of the 64-meter antenna. The parameters of the models were selected on the basis of preliminary design results. For example, the complete antenna model used a 25 percent porous reflector surface for the outer 25 percent radius. However, reflectors with solid, 25 percent porous, and 50 percent porous dishes were tested for their aerodynamic force and moment values. Only the solid and the 25 percent porous dishes were tested for the static pressure values used primarily to determine the wind loading on the reflector's surface panels. The wind loading was then applied to the reflector structural models to determine the rms distortions from a paraboloidal shape, which is useful for radio frequency (KF) gain calculations. As part of the cost reduction effort, the porosity of the dish was increased to 50 percent in the final design so that lower wind designing loads could be used. This caused the generation, by interpolation and extrapolation, of applica- ble force and moment curves for the whole antenna under wind loading. New curves for the static pressure values were also generated. The results, available to date (Ref. 1), show that the force and moment curves were accurate. However, the static pressure curves used for the design proved to be too conservative. This report describes a method for extrapolating the 50 percent porous static pressure data from the solid and the 25 percent porous static pressure values. The accuracy of the result (estimated within 10 percent) should be well within the requirements for structural analysis. 60 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 The verification of the calculating method was proved by first applying it to available solid dish and 25 percent porous dish static wind tunnel pressure data. The answers resulted in a good match between the wind tunnel force and moment test values and the integrated values of the static pressures. Since force and moment values for the 50 percent porous dish from the wind tunnel tests are available, correctly extrapolated static pressure for the 50 percent porous dish, when integrated, should match the wind tunnel values. II. Description The static pressure values were described in Ref. 2 as pressure coefficient differences across a thin paraboloidal surface with a focal length-to-diameter (F/D) value of 0.33. An example is Fig. 1 with the average pressure coefficient difference values shown for the 25 percent porous dish by a solid curve, where the pitch angle is equal to 180 degrees and the yaw angle equal to zero. In other words, the wind is blowing along the symmetric axis of the dish into the convex side. The solid curve represents the average of the static pressure readings of the pressure tap locations shown in Fig. 2. Working toward the solution of the static pressure values for the 50 percent porous dishes, static pressure orifices located on a sample porous plate were tested by the Thermophysics and Fluid Dynamics Section in a small wind tunnel available at JPL. The results showed that the static pressure accurately measures the pressure differ- ences across the 50 percent porous plate placed in a wind stream. Figure 1 shows that the pressure difference coefficient values are higher for the 25 percent porous dish than for the solid. It follows that these values could be higher by the same increment for the 50 percent porous dish as shown by the extrapolated dotted line. To test the accuracy of the static coefficient differences, as applied to the surface panels of a reflector dish, the static pressure data were interpolated for the pitch angle of 120 degrees by use of curves shown in Fig. 3. The sample values for the 15-degree angle row of static orifices are shown in Fig. 4, where only the windward-half values from one column of static orifices are shown. The other half of the dish was very lightly loaded for porous dishes at a pitch angle of 120 degrees. The pitch angle of 120 degrees was selected since the pitching moment is the maximum. Also, since the pressure differences have the largest asymmetry at this pitch angle, the reflector distortion should also be the maximum. A computer program was coded to calculate the solid surface areas applicable to each pressure coefficient difference, followed by integration of the forces with final calculations of the aerodynamic-type coefficients. In Table 1, the wind tunnel test values (Ref. 1) for the forces and moments are- compared with the values computed from the static pressure data from the wind tunnel test values (Ref. 2) for the solid and the 25 percent porous dishes, as well as for the extrapolated curves for the 50 percent porous dish. III. Conclusions The drag coefficients for the wind directly into the front and back of the solid and 25 percent porous dishes between the wind tunnel force tests and the integration of the static data compare very closely as presently computed. Of course, this check was also made during the wind tunnel tests for data verification purposes. This match now also serves to check our computer program and the calculations for the 50 percent porous data. The extrapolated 50 percent porous curve need only be increased slightly in Fig. 1 for a good match of data. For the 120-degree pitch angle case, the values for axial (body axis) force and the pitching moment coefficients match closely. The normal force coefficient from the static pressure data is substantially smaller. The major part of the difference may be explained as follows: As the direction of this component is normal to the symmetric axis of the reflector, there is a wind force existing in the wind tunnel models not present in the static pressure integrating computations. This wind force arises from the wind hitting the sides of the 9.5-mm (3/8-in.) holes in the 3-mm (l/8-in.)-thick dish plate, and is referred to as shear force or skin friction force. The axial force coefficients for the solid dishes from the two methods show some difference, which is still not understood at this time. It is concluded that the extrapolated curves for the 50 percent porous dish will produce accurate aerodynamic coefficient values for paraboloidal dishes of this porosity in the wind. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 61 Acknowledgment The author wishes to acknowledge the contributions of Robert W. Weaver, JPL Thermophysics and Fluid Dynamics Section, for his work in conducting the tests and providing the results on the sample porous plate, for his general review of this report, and for his many helpful comments. References 1. Fox, N. L., and Dayman, B., Jr., Preliminary Report on Paraboloidal Reflector Antenna Wind Tunnel Tests, IM CP-3, Feb. 28, 1962 (JPL internal document). 2. Fox, N. L., Load Distributions on the Surface of Paraboloidal Reflector Antennas, IM CP-4, Feb. 28, 1962 (JPL internal document). 3. Katow, M. S., and McGinness, H. D., "Wind Load Predictions for the 64-meter- diameter Antenna," in The Deep Space Network Progress Report, Technical Report 32-1526, Vol. XV, pp. 96-101, Jet Propulsion Laboratory, Pasadena, Calif., June 15, 1973. 62 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 1. Aerodynamic coefficients of thin paraboloidal dishes Configuration Solid A B 25% porous A B 50% porous A B Pitch = 0° Yaw = 0" cu AXIAL 1.50 1.52 1.17 1.30 0.83 Pitch = 0' Yaw = 180° C ' - 'AXIAL -1.02 -1.05 -0.94 -0.96 -0.83 -0.77 ' 'AXIAL -0.187 -0.280 -0.321 -0.349 -0.294 -0.293 Pitch = 60°; Yaw = 180° c ' - 'NORMAL 0.195 0.166 0.203 0.149 0.217 0.125 ^MOMENT 0.127 0.129 0.109 0.116 0.093 0.097 F/D = 0.33; moment center at paraboloid's vertex A = values from wind tunnel's force data B = values from pressure coefficient difference integration ^ \ X I \ L > CXORM\L ' CMOMEXT = body axis force and moment coefficients JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 63 -0.5 -i.o o t— UJ U 8 -1.5 -2.0 -2.5 25% UNIFORMITY POROUS SURFACE PITCH ANGLE = 180° YAW ANGLE =0° FOCAL LENGTH DIAMETER 0.330 Ko 9=0° 0.50 0.25 0 0.25 RADIAL DISTANCE/DIAMETER Fig. 1. Pressure coefficient differences across a thin parabo- loidal 25 percent uniformly porous surface at pitch angle of 180 deg 45° 105° GROUND SURFACE 0.064 DIAMETER LOOKING INTO CONCAVE FACE AT ZERO PITCH AND YAW ANGLES A PRESSURE TAP ON CONCAVE SURFACE A PRESSURE TAP ON CONVEX SURFACE Fig. 2. Pressure tap locations on model 64 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 1.8 1.6 1.4 1.0 0.8 0.6 0.4 0.2 -0.5 O 1.0 AND 0.76 RADIUS D 0.53 RADIUS A 0.31 RADIUS V 0.1 RADIUS U -1.0 Z Si!y 8 1-1.5 90 80 70 60 50 40 30 20 ANGULAR POSITION , deg 10 Fig. 3. Pressure coefficient difference: interpolated values -2.0 -2.5 PITCH ANGLE = 120° 15° ANGULAR POSITION ORIFICES (WINDWARD HALF ONLY) A SOLID O 25% POROUS 50% POROUS \ \ 50 RADIUS, % 100 Fig. 4. Pressure coefficient difference at pitch angle of 120 deg JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 65 N76 14305 RF Automation Demonstration R. B. Crow R. F. Systems Development Section The radio frequency (RF) automation demonstration was conceived to gather data for a life cycle study to evaluate the cost and operational effectiveness of automation. The RF automation demonstration, as originally envisioned, performs a very important function of " qualifying" the system in that it checks both the necessary conditions (i.e., that the receive/transmit system can be configured and calibrated) and the sufficient conditions (by automatically acquiring the carrier and subcarrier). Continuous monitoring also allows real- time repair of those "necessary conditions" (relay operation, references, etc.) so that the system can be maintained at a higher level of readiness than is now possible. I. Introduction The RF (radio frequency subsystem) automation demon- stration was conceived to gather data on an operational system so that criteria for managing DSN automation could be developed. The RF "subsystem," consisting of the microwave subsystem, two Block IV receivers and one exciter, two Block IV Subcarrier Demodulator Assemblies (SDAs), the noise-adding radiometer (NAR), and the 400- kW S-band operational transmitter located at DSS 14, was chosen since the hardware evolution made automation possible, and the administrative control for the develop- ment of this equipment was contained primarily within one section. Each subassembly was capable of either manual or computer control (selected by a front panel configuration switch). A computer was used to control each type of subassembly while system control and coordination were performed by the RF demonstration computer. The RF automation demonstration, as originally envisioned, performs a very important function of "qualifying" the system, in that it checks both the necessary conditions (i.e., that the receive/transmit system can be configured and calibrated) and the sufficient conditions (by automatically acquiring the carrier and subcarrier). Continuous monitoring also allows real-time repair of those "necessary conditions" (i.e., relay opera- tion, references, etc.) so that the system can be maintained at a higher level of readiness than is now possible. II. Demonstration Plan The RF automation demonstration was managed by developing a functional requirements document describing the scenario for the RF automation demonstration, 66 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 software standards, a development schedule, and man- power assignment. Each subassembly controller software design was reviewed to assure compliance with the functional requirements before further development was undertaken. Maximum checkout at JPL was attempted to minimize the DSS 14 installation and checkout time. Figure 1 is a functional block diagram of the RF system automation demonstration configuration. Each of the major subassemblies shown was controlled by its own computer; system control and coordination were per- formed by the RF demonstration computer, which also served as the operation interface. The remainder of this report defines the original demonstration ground rules and reviews the actual demonstration performed at DSS 14. Observations and data on the experiment are listed. The report concludes with a summary of the important data of this demonstra- tion, a proposed plan for future work, and criteria for future automation implementation. III. Demonstration Ground Rules A functional requirements document for the RF automation demonstration was written, setting forth the following ground rules: (1) All software would be top-down design, imple- mented in a high-level language using structured programming. (2) Available research and development (R&D) comput- ers would be utilized (three PDP-11/20 minicomput- ers and one Intel 8080 microcomputer; see Fig. 1). (3) The hardware interfaces between existing hardware and subsystem controllers would not be changed from those existing prior to this demonstration. (4) The hardware interfaces between subsystem control- lers and RF demonstration controller would be new installations utilizing the DSN standard 14-line interface and standard teletype. (5) The interface between the operator and the RF demonstration controller would be simple English words. (6) The RF demonstration computer would accept all configuration messages from the operator and distribute them to the correct subsystem controller. The RF demonstration controller would receive the necessary feedback from the subsystem controller and perform all necessary coordination between subsystem controllers to effect automatic configura- tion, calibration, acquisition, and failure backup. (7) The RF demonstration controller would appear transparent to each subsystem controller in that diagnostic messages from each subsystem controller would be printed at the operator terminal exactly as sent by the subsystem. In this way, the design of diagnostics in the subsystem controller would not impact the design of the RF demonstration control- ler. (8) Polling of the interfaces would be used to communi- cate between computers. IV. Description of the RF Automation Demonstration The RF demonstration controller was programmed to execute five phases of operational sequences which are described in the following paragraphs. Figure 2 is a flow diagram describing the demonstration software. BEGIN. To begin a mission, the RF demonstration controller polled the subassembly controller to determine which of the subassembly devices were under computer control. The RF demonstration controller then sent a message to the operator indicating which devices were under computer control. The transmitter controller was then directed to turn on the filaments and coolant system, and to check all monitor facilities and the crowbar safety device. During this time, the Block IV SDAs were directed to calibrate so as to determine their operational status. When the transmitter became ready for pre- calibration (PRECAL) and both SDAs had been internally calibrated, the operator was notified to load the mission configuration into the RF demonstration controller's paper tape reader and type 'GAL' to begin PRECAL. PRECAL. The mission configuration data were read in from a paper tape. The RF demonstration controller then sent all configuration messages to the appropriate subassembly controllers. After the messages had been received and acknowledged by the subassembly controller, the RF demonstration controller then sent calibration commands. The noise-adding radiometer (NAR) was used to automatically measure system noise temperature. These data were sent to the receiver controllers where they were available to determine the signal power in the automatic-gain control (AGC) calibration process. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 67 The RF demonstration controller coordinated the calibration phase by monitoring the status and issuing calibration commands at the appropriate time (i.e., after RCV 3 had completed calibration, SDAs 5 and 6 were commanded to calibrate with reference to RCV 3). The operator was kept apprised of the progress of the calibration sequence by messages from the subassembly controller (through the RF demonstration controller) which were displayed on the operator's CRT control unit. When all subassemblies were calibrated, the RF demonstration controller issued a standby command. The operator was then prompted to start the mission (by typing 'START'). OPERATE. When the operator typed a 'START' command, the transmitter was turned on and an automatic carrier acquisition sequence was initiated. The operator (and the RF demonstration controller) was notified by message generated by the receiver controller when each receiver had acquired. The RF demonstration controller automatically commanded the appropriate SDA to acquire once its input receiver was in lock. The operator was informed when each SDA acquired lock. During this phase of the mission, the noise-adding radiometer automatically measured the open-loop gain of the maser preamplifier and front end of the S-band receiver. Changes in gain (greater than 0.02 dB) were sent to the receiver in order that the signal power versus AGC calibration could be corrected so that a more accurate carrier power estimate was available. Each subassembly controller maintained a constant monitor on the "necessary" conditions for operation. If a failure was observed, the subassembly controller automati- cally reconfigured the appropriate subassembly to the predetermined (part of the original configuration input) backup configuration. The operator (and the RF demon- stration controller) was notified of the configuration change and automatic acquisition was initiated. The operator then received the appropriate diagnostics/ instruction to repair the failed unit. The RF demonstration controller coordinated reacquisi- tion (i.e., when a receiver failed, not only must it be functionally replaced with its predetermined backup, but the necessary configuration changes must be made to the SDAs to accept a new receiver input) and subsequent reacquisition of the carrier and subcarrier. The operator terminated the mission by typing 'HALT' which automatically started the post-calibration (POST- CAL) sequence. POSTCAL. The operator's 'HALT' command caused the transmitter to turn off. When the transmitter controller confirmed that the transmitter was in standby, the RF demonstration controller initiated a post-calibra- tion sequence by first configuring the microwave equip- ment and then issuing post-calibration commands to the transmitter, receiver-exciter, and SDA subassembly controllers. A similar sequence was followed as in pre-calibration (i.e., the RF demonstration controller coordinates the receiver and SDA calibration sequence). Noise tempera- ture was automatically obtained from the NAR as in pre- calibration. When all subsystems had completed post-calibration, the operator was prompted to type 'RESTART' to run another mission or type 'END' to secure the RF subsystem. END MISSION. The transmitter controller was com- manded to secure the transmitter (i.e., an orderly turnoff sequence in which the coolant system cools the power amplifier before turning itself off). All other subsystems were placed in a "standby" configuration. V. Demonstration Results and Observations The receive channel (i.e., the antenna microwave subsystem, Block IV receiver-exciter, Block IV SDA, see Fig. 1) successfully demonstrated automatic configuration, calibration, and acquisition (both carrier and subcarrier) of a simulated signal during the first tests. The transmit channel was not tested during this time (due to a hardware failure of the 400-kW S-band operational transmitter). However, a later demonstration was run with the 400-kW R&D transmitter, where automatic configuration, calibra- tion, and output power control were successfully demon- strated. Several observations made during the RF automation demonstration effort are listed below to document some of the more interesting characteristics. (1) Actual Time to Automatically Control the Receive Channel. The BEGIN phase took 6 to 7 minutes to poll all controllers and internally calibrate the Block IV SDAs. 68 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 The PRECAL phase took 6 to 8 minutes to input and distribute the mission configuration data and an additional 10 minutes to calibrate receivers 3 and 4 (the receivers were calibrated in series) and 0.5 minute to calibrate SDAs 5 and 6. This performance was far slower than the original estimate of 5 minutes for a complete PRECAL sequence. Future effort will be directed at reducing the PRECAL and configuration time. (2) Intra-computer Communications. Software imple- mentation of data transfer over a 14-line interface was used. This routine was written in both RT-11 (DEC) BASIC and PL/M (high-level language used in the Intel 8080). The BASIC software data transfer was very slow (6 bytes/second). The PL/M software, when transferring data to the Block IV SDA, operated at 600 bytes/second and should operate at 300 bytes/second if transferring data to another 8080 microcomputer. Polling was used in lieu of interrupts in an attempt to simplify the software development and determine if polling performance was adequate for real-time hardware control of this type. It was found, however, that polling is probably the largest contributor to the poor communication speed, since as much as one minute was spent waiting for some of the controllers to process a message before accepting new data. This characteristic became a serious problem when it was necessary to continue handling low priority (diagnostic) messages while operational "action" messages were left waiting for several minutes. Both 14-line and serial interfaces were used during the demonstration. No known noise or communica- tion failures were noted. One hardware failure occurred, and a possible "start up" problem in the serial interface hardware was noted. (3) Program Size/Development Time. Table 1 indicates the size of each program and the approximate software development effort. Several factors should be considered when reviewing these data: (a) The RT-11 operating system had software bugs in its "overlay" option that forced the RF demonstration program to be rewritten to achieve a reasonable software reliability. (b) The PDP-11 's with the large number of unibus loads (i.e., Dectape, several digital input/output (I/O) interfaces, analog-to-digital converter (ADC), teletype (TTY), etc.) were unreliable. Random system failures occurred with no known hardware failure to explain them. During the course of the demonstration, several hardware failures did occur (i.e., memory failure, TTY failure, paper tape reader failure). The PDP-ll's poor reliability record stood out in stark contrast to the 8080 microcomputer which has operated without failure since its purchase in December 1974. (c) The RT-11 operating system required 10.5 kilowords of core. The core requirement of the programs (listed in Table 1) required "chaining" in all PDP-11 computers except the receiver- exciter controller where 24 kilowords of core existed. (d) Proper structuring of the software from both the instructional and data viewpoints was hindered by the use of RT-11 BASIC and the lack of memory. For example, in the receiver-exciter controller, sets of bits had to be packed into floating point variables conserving core, but creating awkward, time-consuming BASIC con- structs to manipulate them. (4) Operational Effectiveness. The demonstration pointed out the need for more flexible operator controls so that nonstandard operations could be bandied (i.e., it should be possible: (a) to change the receiver's acquisition characteristics by merely typing "RCV 3, A/ - -100 kHz" and lower the original S-band acquisition window by 100 kHz, (b) to change the receiver doppler rate, and (c) to change SDA symbol rate and modulation index by similar high-level operator inputs, etc.). (5) High-Level Language. RT-11 BASIC was used for all controllers except the SDA controller (which used PL/M). The BASIC language was slow, had no capability for bit manipulation (required in configu- ration control), and was not well suited for structured programming. PL/M is a high-level language currently available as a cross compiler installed in the Univac 1108 to generate code for Intel 8080 as compiled object code. PL/M provides a more favorable speed and memory characteristic than does the RT-11 BASIC. The present PL/M operating system contains a two- pass compiler and an 8080 simulator. This facility is flexible and was used with good results for correct- ing a software problem while at DSS 14. (6) Top-Down, Structured Design. This design method produced efficient readable code. Changes were JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 easily made (due to modular code that resulted from using a structured design). VI. Summary of the RF Automation Demonstration Lack of operational reliability was the single most troublesome factor in demonstrating automation feasibil- ity. The importance of reliable hardware and software with built-in fault isolation and diagnostic capability was recognized and will be incorporated into future designs. A much better understanding now exists of the needed operator controls and the environment in which they are used. The RF automation demonstration served as an excellent "breadboard" in that it offered a stage where several concepts turned out quite well (i.e., top-down, structured software design, use of 8080 microcomputer utilizing the PL/M language, etc.), while others turned out quite poorly (i.e., BASIC was a poor language for this demonstration, polling did not work satisfactory, the PDP- 11's were unreliable, etc.). VII. Recommendations Automation should be implemented when: (1) The automation controllers to be implemented are reliable enough so that the added burden imposed on the station is more than offset by improved performance and station availability. (2) The system is flexible enough to permit the operators to handle all nonstandard events that are presently accomplished. Other general recommendations are: (3) Polling should not be used; instead the system should be interrupt driven. (4) Future interface hardware design should contain built-in fault isolation aids to facilitate system repair. (5) Failure analysis and automatic functional backup should save valuable mission data while the subas- sembly diagnostic should minimize down-time and so should be actively pursued. (6) RT-11 BASIC is too slow for a real-time control system. This observation coupled with the poor reliability of the PDP-11 hardware and software indicate the PDP-11 should not be used again as the controller. (7) The PL/M language used by the 8080 appears efficient in time and memory and should be used in another demonstration. (8) Adequate memory should be planned for. (9) In the foreseeable near future it seems wise to concentrate on providing the operators with im- proved tools (i.e., useful macro commands, RCV 3:A/ = -100 kHz, OOP = 200 Hz) without trying to solve costly operational problems that occur infrequently (i.e., it would be possible to conduct an automatic organized search of carrier, subcarrier, symbol rate in the event of major trauma to the spacecraft; however, our current state of develop- ment does not as yet offer this capability as a cost- effective option). (10) Software standards should be created using top- down, structured design with a high-level language so that eventually one software sustaining engineer could maintain the RF subsystem software. VIII. Future Plans A second RF automation demonstration is presently planned for April 1976. This demonstration will follow the basic plan established for the first demonstration but will emphasize system reliability, operator flexibility, and improvement of the automation data base. A preliminary study will be undertaken to determine the current stage of hardware automation in each major subassembly and will present management options for future automation. 70 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 1. RF demonstration program size/development time Controller name Demonstration configuration RF demonstration Receiver— exciter Transmitter SDA Microwave Total number of BASIC or PL/M statements 1250 1050 1000 700 650 200 Core requirement in 1000 16-bit words 14 10 10 10 9 ( 8-bit words ) 4 Software development time, man days Design 40 35 20 50 30 10 Code 15 20 10 15 15 2 Debug 25 60 25 50 10 5 Computer type/language PDP-11 BASIC PDP-11 BASIC PDP-11 BASIC PDP-11 BASIC 8080 PL/M PDP-11 BASIC ORIGINAL PAGE IS OF POOR QUALITY JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 71 XMTR CHANNEL l:"""""l RCVR CHANNEL CONTROL INSTRUMENTATION Fig. 1. RF automation demonstration functional block diagram 72 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 C RF DEMO J BEGIN • POLL SUBASSEMBLY CONTROLLERS FOR MANUAL/COMPUTER CONTROL • TURN ON HIGH-POWER TRANSMITTER • MISSION-INDEPENDENT PRECAL OF BLK IV SDA PRECAL • INPUT CONFIGURATION • CALIBRATE TRANSMITTER, RECEIVER-EXCITER • CALIBRATE SDA OPERATE TURN ON TRANSMITTER ACQUIRE f ACQUIRE f MONITOR FAIL BACKUP/DIAGNOSTICS POSTCAL • CALIBRATE CONFIGURATION • POSTCAL TRANSMITTER, RECEIVER-EXCITER • RF SYSTEM IN STANDBY NO END TURN OFF TRANSMITTER MISSION-INDEPENDENT POSTCAL OF BLK IV SDA ( ENDMISSION Fig. 2. Flow diagram of RF demonstration control program JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 73 Transmitter Automation R. M. Gosline R. F. Systems Development Section As part of the radio frequency automation demonstration, the transmitter subsystem at DSS 14 was automated to perform a simulated spacecraft mission with pre-mission and post-mission calibrations. Schedule and budgetary restrictions required the use of existing hardware wherever possible. A PDP-11 minicomputer was available and used for the subsystem controller. I. Introduction As part of the radio frequency (RF) automation demonstration, the transmitter subsystem at DSS 14 was automated to perform a simulated spacecraft mission with pre-mission and post-mission calibrations. Schedule and budgetary restrictions required the use of existing hardware wherever possible. A PDP-11 minicomputer was available and used for the subsystem controller. II. Hardware Description Three junction boxes were installed in the pedestal research and development (R&D) control room near the R&D remote control console (RCC). All monitor and control lines were switched with three rotary switches, enabling the station to return easily to the normal configuration. Logic level converters were used to interface the 28-volt transmitter control logic to the standard 5-volt transistor-transistor logic (TTL) used by the PDP-11. The PDP-11 monitored 64 input lines, 10 analog channels, and provided 19 command lines. The 14- line interface was converted to a serial bit pattern requiring only two twisted pairs for the 370-meter (1200- foot) communication cable to the demonstration control- lers located in the DSS 14 control room. A converter at the other end converted back to standard 14 lines. The PDP-11 was equipped with an analog-to-digital converter and a 16-channel multiplexer. The memory size was 16,384 although only 6,000 was available for the control program. A Dectape dual magnetic tape drive was also available. III. Software Description The major part of the project involved software development. Top-down structured programming princi- ples were followed, and most of the programming was done in DEC RT-11 BASIC. Even the standard 14-line interface algorithm was implemented in BASIC as a last resort when assembly language routines failed to' link string variables properly. Although reliable, only 5 ASCII characters were transferred per second between comput- 74 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 ers. The program was designed to decode and act on six commands from the demonstration controller as follows (Fig. 1). INT: The initialize command caused the subsystem to indicate status (manual mode or computer control) to the demonstration controller. If in computer mode, the control power supply, the coolant system, and the filaments were turned on, starting the five-minute filament time delay. CFG: A configuration command indicated that power and frequency data were following. The received values were checked for proper range and converted for internal use. CAL: A calibration command would be rejected if INT and CFG were not complete. If accepted and in the waterload position, the crowbar logic was tested, perveance data obtained, and klystron saturated by manipulation of the beam voltage and drive power. Verification of the power meter calibration at the mission power level was checked. Finally, the beam was turned off and the standby state entered. STB: The standby state could be commanded at any time provided CAL had been completed. P\VR: The power command caused the beam voltage to be turned on to the value specified in CFG provided CAL had been completed. The value of output power was reported to the demonstration controller. OFF: An off command was only accepted if not in PWR state. An orderly shutdown was performed, allowing time to cool the klystron before shutting off the coolant system. Finally, the computer executes a stop command requiring manual intervention to restart. All command messages were echoed to the demonstra- tion controller, if possible, otherwise placed on the message output queue to try later. When not performing commands or handling messages, the program entered a monitor loop in which the subsystem parameters were compared to those expected. Anomalies were acted upon, if possible, and reported to the demonstration controller in any case. All analog channels could be corrected for slight drifts without mission interruption. Transmitter interlocks would be reset three times before issuing a diagnostic message requesting manual assistance. IV. Performance Many difficulties were encountered with the PDP-11, even though the computer had been reconditioned at the vendor facility. Many RT-11 operating system problems were also discovered for which the vendor could not find solutions. The second major problem was communication speed due to the software 14-line interface and a polling system instead of interrupts. Long messages could tie up the demonstration controller for minutes while others were polling to see if the controller was ready to listen. In spite of these difficulties, an automated system was demonstrated, although the klystron saturation algorithm was not completely verified in the demonstration. V. Conclusions ; It should be pointed out that although the automation demonstration provided much data and experience at the system level, few improvements were made within the transmitter subsystem. Instead, the operator was au- tomated at the control panel. There are undoubtedly greater benefits to be obtained by designing certain devices and techniques into the equipment first; then integration into a system demonstration becomes a relatively easy task. The top-down structured programming technique is a useful method but the rules must be followed rigorously even under schedule pressure to obtain the maximum benefits. An interrupt system, rather than the polling technique, would greatly improve program execution. The BASIC language, because of its resident compiler, does not seem to make efficient use of core or machine time. Also, bit manipulations and special device input/ output operations are difficult. An assembly language program would seem to offer more advantages as well as preserve the on-line near-real-time correction capability. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 75 /TRANSMITTER( CONTROL \PROGRAM Fig. 1. Transmitter control program top-level flow chart 76 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Automatic Microwave Configuration Control J. G. Leflang R. F. Systems Development Section Several radio frequency subsystems were recently operated at DSS 14 using minicomputers for data input, calibration, control, monitoring, and failure backup and diagnosis. As part of that test, the microwave configuration control portion of the antenna microwave subsystem was interfaced with a PDP-11/20 computer. I. Introduction Recently, practical computer control and monitoring of several radio frequency (RF) subsystems was demonstrated at DSS 14. A portion of the antenna microwave subsystem, the configuration control group, was included in the demonstration. The equipment in the configuration control group provides a means of controlling and reading 120 switch positions. Approximately 80 switch positions are presently used. II. Hardware Design Switch control is manually accomplished by actuating a push-button that completes a dc return path for one coil of a set of relays which control the 110-volt ac power applied to the microwave switch motors. The computer interface utilizes an open collector peripheral driver connected to the dc return path for each relay in a wire- OR configuration (Ref. 1). Thus, either manual push- buttons or the peripheral drivers may be used to actuate relays (and thereby switches) in the configuration control hardware. Switch position indication is accomplished by using a 24-volt dc signal to illuminate the manual push-buttons which correspond to the switch position. The original technique for controlling and monitoring switch positions used opto-isolators for noise rejection and for shifting to transistor-transistor logic (TTL) levels (Ref. 1). Field tests using the original design equipment proved that the opto- isolators were unnecessary, and the equipment used for the RF demonstration used lower cost resistive voltage dividers for shifting from 24 volts dc to TTL levels, and did not use opto-isolators in the peripheral driver circuits. The computer interface assembly is composed of a DSN standard interface, a function decoder, and five 24-bit shift registers. The shift registers provide 120 parallel outputs which drive all five switch groups (bays) within the JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 77 configuration control hardware. The function decoder reads three bits of each input byte to determine the required function. Of the eight possible function codes, five are used. The functions are: (1) Output six data bytes which contain information on power supply status and the state of a computer input enable/disable flip-flop. (2) Output 24 data bytes which contain information on the output state of all shift registers. (3) Enable relay driver outputs. (4) Disable relay driver outputs. (5) Output 24 data bytes which contain information on all switch position indicators. The use of a three-bit function code of value zero causes the shift registers to accept configuration data. III. Software Design The configuration control software was designed as two modules that are part of a nonreal-time sequence of processes which combine the receiver and microwave software in one computer. Coding was done in Digital Equipment Corporation's RT-11 BASIC. Configuration commands are received as strings of two- digit numbers. Each number represents a macro configu- ration which is a useful functional portion of some configuration required for operations. One of the two software modules, the input message processor, segments the command string and validates each command. Valid commands are stored in a prime command stack if not specifically identified as a failure backup command by the prefix "FB." After the command string is stored, the stack is scanned one command at a time, and the corresponding macro is overlayed into an array which is then shifted in 24 bytes into the hardware registers. The registers are tested by reading back into the computer and comparing them to the macros specified in the prime command string. If the registers are properly loaded, an enable command is given to drive the switch control relays. This process is repeated for all storage cells in the command stack. Any register error is reported as a macro failure. The second module provides a periodic monitor of switch positions specified by the command string. Switches not specified are not monitored. This module reports any discrepancies, loads the failure backup command, if any, into the prime command stack, reloads and tests the shift registers, enables the relay drivers, tests the switch position indicators for correct position, and reports the backup action to the monitor console. IV. Results The configuration control hardware operated reliably and precisely as intended. All circuits appeared to have noise margins which are adequate for operation in the station environment. In spite of the 305-meter (1000-foot) cable runs, opto-isolators were not required, but it should be pointed out that noise, not ground loops, is the only concern because the relay coils and contacts used for indicators are not grounded to the antenna. Similarly, the software functioned well. However, core size restrictions prevented the use of extensive diagnostic routines. Also, the macro configuration tables were originally stored in magnetic tape virtual memory because of the shortage of memory. However, the long access time associated with reading a file from the tape prompted a software modification which stored the macro tables in memory. Prior to the modification, it was possible to consume many minutes performing diagnostics and failure backups. At first, manual override of a computer-generated configuration required that the switch in question be moved twice because the computer would attempt to restore the original configuration once after any manual change. This proved to be very annoying, and the software was changed to permit human operators to move switches at any time. However, any manual operation which alters a computer-specified configuration still is detected by the computer and is identified on the display console. V. Conclusions Automatic configuration control of the microwave subsystem is feasible. We have developed a simple, compact, and reliable hardware design that interfaces the configuration control group with any computer which has a DSN interface and can support the necessary software. The use of software instead of hardware is very desirable for the purposes of establishing and testing functional combinations of switch positions (modes). The resulting hardware is low cost, and the software provides the flexibility necessary to adjust to changing mission require- ments without large monetary expenditures. The software functioned fairly well, but it did prove to be unreasonably slow and to require a large amount of 78 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 memory to store the system executive and the basic in the microwave subsystem. There are other languages interpreter (21.2 kbytes). which offer speed and compactness, and the use of one of these will permit a hardware/software package which will Because of low speed and large memory requirements, prove to be of substantial value to operations and will not BASIC is not attractive as a programming language for use carry a prohibitive price tag. Reference 1. Leflang, J. G., "Automation of Microwave Configuration Control," in The Deep Space Network Progress Report 42-21, pp. 59-64, Jet Propulsion Laboratory, Pasadena, Calif., June 15, 1974. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 79 Three-Dimensional Plotting on a Two-Dimensional Surface S. K. Skedzeleski Communications Systems Research Section Data collected over a two-dimensional surface are often test-displayed as a surface whose height above the plane represents the functions value at the corresponding coordinates. One algorithm for producing such a plane is described, using horizontal lines to define the surface. It has been implemented as a FORTRAN subroutine on the SDS 930 computer. I. Introduction It is often desirable to display data which are a func- tion of two variables as a surface whose height above the coordinate plane represents the function's value at the corresponding coordinates. A very simple algorithm has been used for several years to display the results of radar mapping, but it has been done ad hoc and built directly into each program as it was needed. A FORTRAN sub- routine which is very brief, both in time and space, has been written to do this plotting on the SDS 930 computer. The subroutine, ODD, takes data one line at a time (in the constant Y direction) and outputs line segments to the plotting routines that are available on this system. One initialization call is needed to set the boundaries of the plot, and such information is passed in blank COM- MON. It would be better to logically separate it in a labeled COMMON block, but RTFTRAN on the 930 computer does not have that capability. II. The Algorithm For reading clarity, the following notation is used: fT I / the function value at (x,y) z*.v y + fs.i, NX number of points in the x direction Ax spacing between sample points in the X direction Ay spacing between sample points in the Y direction The algorithm used in DDD is very simple. For each point (.r,j/) a line segment is drawn from (x — Ax.Zj.-^.y) to (x.Zj..„). The first point of each line is handled differ- ently from the rest of the points since the pen is merely positioned there. This algorithm does not conceal hidden 80 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 lines. A first-order improvement is easy to implement by keeping track of the maximum value of zx-.v- for each x' = xm i n , x m j n + Ax, •••,xm<1 , , over y' = ym i n ,ym in + Ay, • • • , y c i < r r e n f (initially zero). This is done in the array ZMAX (length NX). If the current point is hidden (i.e., z,:V < ZMAX,), then do not draw the line segment, but move the pen to (x,zI:V) with the pen up. This produces acceptable plots when the grid size is not "too large." An improvement that is used in DDD is to try to deter- mine at what point a line disappears and to draw the visible portion of the line segment (x — Ax.z^-Ar.j,), (x,zr,v). This is implemented by keeping an extra array of length NX, called ZMAXPREDECESSOR. ZMAXPREDECES- SOR gives the position of the other end of the line seg- ment drawn to ZMAX, for each x position. (This is not totally true. If the line segment just drawn is a partial line segment—because the previous point was a'hidden point—the value is still ZJ--AJ-.,,, not the point at which this line segment became visible). One more value, ZLAST (= ZJ.-AJ-,!,), is needed to calculate the point at which lines became visible and hidden. There are two cases which must be considered: a line disappearing and a line reappearing. In Case I, the current point is hidden, but the last point was visible (line disappearing). In the drawing be- low, the line segment (z2,z3) was drawn previously; Zj was the last point, and z4 is the current point. We wish In Case II, the current point is visible, but the last point was hidden (line reappearing). In the drawing be- low, the line segment (z1; z4) was drawn previously; z2 was the last point, and Z4 is the current point. We wish to move the pen (still up) to point c, then move to the point z3 with the pen down. Setting zt = ZMAXj._Aj, z2 = ZLAST, z3 = zz.y and z4 = ZMAX,, we can substi- tute into the formula in Case I and determine point c. A. Caveat It should be noted that this method of removing hidden lines is not foolproof. There are situations in which it will cause a line segment to extend past another already drawn. Specifically, if between x — Ax and x the line seg- ment which ends at (x, ZMAXf) is not above all other line segments in that interval, an error can occur (see follow- ing sketch). The line segment drawn should be hidden, to add the line segment (z,,c) and then move the pen to z4 with the pen up. Setting Zi = ZMAX(x — Ax), z2 = ZMAXPREDECESSOR;, z, = ZMAX, and z4 = z, „, we see that we must have zl + a (z, — zj = z2 + a (z3 — z2), where a is the fraction of Ax from x — Ax to Ax where the line segments cross. Solving for a we get a = z, — z2/ Zi — z2 + z3 — z4, which gives the crossing point c = (x - Ax + a • x, z, + a (z3 — Z2)). yet DDD will draw it. In practice, this situation does not seem to occur often enough or with enough visual impact to justify doing a better job than is now done. However, it was found that by simplifying this procedure further by not keeping track of ZMAXPREDECESSOR and using ZLAST instead, obnoxiously visible crossings were occur- ring on almost all transitions from visible to hidden points. Hence the current degree of detail. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 81 B. Sideviewing The algorithm described so far is for a view of the surface which is directly in front of and slightly above the surface. The angle of view depends on rate of change of Y with vertical height and hence is essentially pro- grammable. With certain kinds of data it is necessary to view the surface from a slight angle instead of head-on. One method of doing this is to offset each line in con- stant Y by one or more Ax positions. It is then possible to "peek around" tall parts of the surface. It is easy to modify the algorithm described so far to allow this. It suffices to keep ZMAX indexed on the position of the plotter, rather than having it coincident with a given x position. The points are then plotted at x + x0ffset, and *„//««« is incremented as each line is finished. C. Edge Lines If only horizontal lines are drawn, as in DDD, the line segments will be dangling on each end. It is particularly annoying on the near edge when side viewing is used, since this is where the eye expects to see the effects of "slicing" this portion of the surface from the entire sur- face. By adding a line segment from the last point of the current line to the last point of the previous line, the edges are effectively tied down. The edge on the far side is more difficult to connect since there are noticeable (bad) effects from connecting hidden points. III. User's Guide To draw a surface containing NX by IVY points, NY + 1 calls are made to DDD. The first call initializes variables used by DDD, and the remaining calls actually draw the surface. Before the first call is made, the following vari- ables in COMMON must be given values. COMMON XLIM,YLIM,NX,XSCALE, HDELT,IRO UTEJERR XLIM.YLIM the boundaries of the plotting area (in inches for the plotter) NX the number of points across a line XSCALE scaling factor applied to /,,„. It is used to adjust the height of each value above the baseline IYDELT the number of Ax positions to shift each line, for side viewing I ROUTE must be set to 1 Calling Sequence: Call DDD (ARRAY.NY) ARRAY is the array of NY data points to be plotted. The first call to DDD returns the follow- ing values: I ROUTE is set to 2 /ERR returns to 0 if the arrays in DDD are large enough to handle this plot, 1 other- wise. Currently there can be 512 Ax posi- tions across the entire page (not across just one line of the plot). Each succeeding call to DDD draws one line across the plot. To restart DDD, set IROUTE to 1, and reset any variables that need to be changed. DDD does not auto- matically advance to a new sheet of paper or do any "non- standard" centering of the plot on the page. 82 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Rapid Access Disks Utility Programs for the SDS 930 Computer S. K. Skedzeleski Communications Systems Research Section This article describes three utility programs for the SDS 930 computer with rapid access disks (RADs). Two of these programs transfer data between magnetic tape and an RAD, and the third is a diagnostic program. All programs operate in a multitasking environment using MULTI, a small 930 operating system. I. Introduction A pair of programs has been written for the SDS 930 computer to supplement the data transfer program MEDIA. It allows rapid access disks (RADs) to magnetic tape to RAD transfers of data. Using these programs, one can selectively save the contents of an RAD in a sector-by- sector tape dump. All or part of the RAD or tape file can be transferred. A simple RAD diagnostic was also written. It uses the 930 multiprogramming task master MULTI (Ref. 1) to perform a read-write-verify test on selected portions of the RAD. It was written to provide our section with an easy to understand diagnostic that can be easily changed as conditions necessitate, and also as a checkout for the 930 version of MULTI. The program is designed to run for long periods of time, and will provide an error summary as output. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 II. User's Guide for RAD Diagnostic There are two parameters necessary to run this program: the range of RAD addresses to test, and the test pattern to use. The addresses are selected by using the RAD's file protection switches. Only those sectors which are not protected will be tested. The pattern to be used is entered on the display and entry panel (DEP) thumbwheel switches (Ref. 2). It is copied into a 64-word buffer, which is written onto the RAD sectors. Another buffer is filled with the ones complement of the buffer just written, and the sector is read back in. The two buffers are then compared word by word, and errors are tabulated by the band number, sector within a band, and word within a sector. To obtain a listing of all errors without stopping the program, the console interrupt button is pressed. A listing of the errors is written on the line printer while the diagnostic continues. 83 C.- III. User's Guide to RADTAPE RADTAPE transfers contiguous sectors from a 930 RAD to magnetic tape. The RAD sectors are dumped in separate records containing sixty-five 24-bit words (the extra word contains the RAD address). The program uses the third version of the multiprogramming task master MULTI to overlap input and output functions. Multiple buffering allows tasking to overlap tape and input/output (I/O) operations. When no other tasks are active, a task is run which allows core locations to be displayed on the DEP device attached to the 930. Sense lights on this panel are also used, with one of ten lights being lit whenever a given task or interrupt routine is being executed. This turned out to be very valuable while debugging the program. The program begins by typing the prompt ENTER TAPE UNIT AND NUMBER OF FILES TO SKIP The user types the logical tape unit selected, and a decimal number of files to skip (zero is acceptable; negative numbers are not acceptable). If the tape is write- protected, new numbers must be entered and the prompt will be repeated. After these values are read, the prompt ENTER RANGE OF ADDRESSES TO DUMP (IN OCTAL) appears. The user gives a range of octal RAD sector : addresses to dump. Two addresses must be entered, and the first address must be less than or equal to the second address. If not, the prompt is repeated and another pair of addresses must be entered. When typing in the addresses, the backspace character will delete the previous digit of the current number being typed. To delete the entire line, the delete character («•) is typed. This causes a carriage return and a line feed to be echoed. The following characters serve as separators of numbers: blank comma dash carriage return More than one number can be entered on a line. For example, the following lines are equivalent: 0,5 0-5 0 5 RADTAPE writes a double end of file after each block of contiguous sectors is written, but back spaces over the second end of file (EOF) after it is written. After this is done, the prompt ENTER RANGE OF ADDRESSES TO DUMP (IN OCTAL) is repeated, and another set of RAD sectors can be dumped. By repositioning the tape in front of the second EOF, single EOF marks will separate blocks of sectors, while the last block is followed by a double EOF. The program is stopped by changing the RUN-IDLE-STEP switch to IDLE, and booting in the system from the RAD. In case of an error detected by the tape controller while writing, the program attempts to rewrite the record three times before erasing that section of the tape and trying again farther down the tape. Instead of backspacing over the record in error, the program skips backward to the previous EOF mark (or bottom of text (EOT) mark) and skips forward over the records previously written. This avoids a problem that can occur when the tape drives are not perfectly tuned. They might then erronously move back into the previous record while backspacing or erasing reverse, destroying part of the previous record. Errors detected by the RAD controller or Y channel cause the message **RAD ERROR** to be typed, and the program halts. IV. User's Guide to TAPERAD TAPERAD transfers sectors previously stored on magnetic tape by the program RADTAPE to the RAD, using the multiprogramming taskmaster MULTI (Ref. 1). The files stored on tape are blocks with contiguous RAD sector addresses, each record containing 65 words. Multiple buffers allow the use of tasks to overlap the input and output operations. As in RADTAPE, a background task is run which continuously displays a location in memory, and the sense lights are used to indicate active tasks. The program begins by typing the prompt ENTER TAPE UNIT The user types the logical tape unit selected, and the program continues by typing 84 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 ENTER NUMBER OF FILES TO SKIP, NUM- BER TO PROCESS A decimal number is entered for each item, and the number to process must be nonzero. If not, the prompt is repeated, and both numbers must be reentered. The second number is used when the user wants to dump several blocks which are on adjacent files: ENTER RANGE OF ADDRESSES TO DUMP (IN OCTAL) The user gives the acceptable upper and lower bounds for sector addresses to be transferred. Entering 0-17777 will dump all records in the number of files specified. If the first address is greater than the second address, the prompt is repeated and the numbers must be reentered. The program now begins skipping any files requested and then transferring any records in the range given above. Three errors can occur: **RAD IS FILE PROTECTED. TOGGLE BPT 4 TO RETRY** The program then loops until the position of BPT 4 is changed, and will try to write the sector again: **RAD ERROR** This is typed when a Y channel error occurs, or the coupler signals an error. The program halts. ENTER 0 TO RETRY, 1 TO USE IT, 2 TO SKIP IT This is typed when a tape error is signalled. TAPERAD tries to read each record at most five times; then it prints the above message and waits for the operator to type a response. 0 causes five more tries, 1 accepts the record as last read, and 2 causes the record to be ignored. The programs RADTAPE and TAPERAD can be used in lieu of SYSGEN, by saving the system, its libraries, and the disk directory. This would be done by writing two files: one from 0 to the last address used by the libraries, and another block to get the directory at the other end of the RAD. To restore the system, the user would process two files, giving the range 0-17777 of addresses to dump. When finished processing the given number of files, the program is ready to continue, and again asks for the number of files to skip to and process. The program is terminated by moving the RUN-IDLE-STEP to IDLE, and booting in the system from the RAD. References 1. Erickson, D. E., and Layland, J. W., "An Experiment in Remote Monitoring of Mu-Ranging Operation at Mariner Mars 1971 Superior Conjunction," in The Deep Space Network Progress Report, Technical Report 32-1526, Vol. XV, pp. 156-166, Jet Propulsion Laboratory, Pasadena, Calif., June 15, 1973. 2. Brokl, S. S., "Computer Display and Entry Panel," in The Deep Space Network Progress Report, Technical Report 32-1526, Vol. IX, pp. 44-48, Jet Propulsion Laboratory, Pasadena, Calif., June 15, 1972. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 85 14306 Doppler Spectrum Extraction of Planetary Radar Data Using Computer FFT and Integration D. E. Wallis Communications Systems Research Section A computer program to extract integrated doppler spectra of planetary radar returns is described. The program input data are discrete, complex-valued time series obtained for each of 64 range gates. The data record is subdivided into successive subseries of 256 time-points, and each 256-point time series is discrete- Fourier-transformed using the fast Fourier transform (FFT). Power spectra are obtained by magnitude-squaring. The power spectra, containing positive- and negative-frequency doppler components, are assumed statistically stationary dur- ing receive-runs of 10 to 15 minutes duration, and so may be (SNR)-enhanced by integration (summation) of successive 256-point power spectra. Program output is a highly compressed power spectrum tape containing 64 integrated spectra, together with identification and parameter values, for all receive runs made dur- ing each day of a total of six days of radar observations of the planet Mercury in calendar year 1974. Brief discussions of the on-site data-taking process and the doppler interpretation of the discrde Fourier transform are included. I. Introduction This report describes a computer program to extract integrated doppler power spectra of planetary radar returns. The description of the on-site data-taking process and data-reduction requirements in Sect. II is used to introduce the detailed descriptions of data-tape formats in Sect. Ill and the computational flowchart in Sect. IV. To anticipate and answer some questions of users of the program, a brief discussion of the doppler interpretation of the Discrete Fourier Transform (DFT) is included in Sect. V. II. Background: The On-Site Data-Taking Process In the radar observations of the planet Mercury in summer 1974, digital complex-valued (quadrature-pair) amplitude samples of approximately 15-bit maximum resolution are obtained from the radar receiver-detector 86 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 system. The detector system has 64 range gates, 32 of which are assigned to Coder 1, with the remainder as- signed to Coder 2. The operations of Coder 1 and Coder 2 are interleaved, so that Coder 1 produces data for even ranges 0,2,4,•••,62 and Coder 2 produces data for odd ranges 1,3,5,-•-,63, where 0,1,2,3,•••,62,63 is the ordering of range itself. At each range assignment, the coders output their complex-valued amplitude samples to the on-site XDS 930 computer, which merges the 128 num- bers from the coders with serial-number, time-of-day, and various experimental parameters to form a 192-word record to be written on standard 7-track tape at 800 bits/inch. Each 192-word record, then, contains 64 com- plex-valued amplitude samples, the set of which may be regarded, for purposes of power-spectrum computation, as representing a vector-valued sample at a single point in time. Two tape drives are operational for the on-site data recording process, so that one drive unit is available on line to the computer while the other unit is being rewound and reloaded. In a given day's observations, 18 to 19 reels of tape are written, and the succession of 192- word records is continuous from each tape reel to the next, except that a 4K-word core dump is always the first record written at the beginning of each reel used. The condition for continuing the data recording onto the available alternate tape drive is, effectively: If not end- of-tape, write to present unit; if end-of-tape, switch units, write a core-dump record, and resume data recording without loss of continuity. Because of variable distances to the planet under observation, the number of records written during each receive-run (duration of approx- imately one round-trip-light-time) varies. To maximize utilization of recording tape, the recording process is suspended in mid-tape at the end of a receive run, so that recording may resume without loss of footage as data from the next receive run become ready to record. Each 192-word, time-point record contains a serial number which serves, along with a notation of time-of-day for each record, to ensure that data for truly successive points in time can be identified in the subsequent data reduc- tion. The boxes of tapes for a given day's observations are accompanied by a computer typeout of the serial num- bers marking the ends of the successive receive-runs, together with other station log information not used in the present program. A. Requirements for the Data Reduction Program The computer program to be described in the follow- ing must, of course, contain program logic to read data tapes organized as described above. Additionally, the program must anticipate and guard against possible errors in the on-site data-taking process which, due to heavy real-time computational demands, cannot be cor- rected on-line without incurring other unacceptable losses. A further requirement on the present program is to produce intercomputer compatible output, so that the power spectrum tapes to be produced are suitable for dissemination to users demanding high confidence in data validity and processing integrity. Embedded within the above requirements, are the more purely mathematical operations of the discrete Fourier transform, spectrum computation, and spectrum integration. The Fourier transform is accomplished by the now traditional FFT technique, and program require- ments reduce to ensuring that computations are correctly scaled, free from overflows, that spectral extraction is correct, and that output formats are as specified. III. Input and Output Tape and Record Formats Input to the computer program comprises time tapes generated at the station, plus certain entries obtained from the radar log, which are typed into the computer at processing time by the computer operator. Output from the computer program is an intercomputer compatible spectrum tape, incidentally accompanied by a computer typ^out of important processing milestones, plus a record of occurrences of computational overflow. The input and output tapes are 7-track, 800 bits/in, and their formats are given in Tables 1-4. Explanatory remarks are in- cluded with the figures. Section II (q.v.) may be consulted in connection with the time tape formats. The content of the spectrum tape header records is for the most part copied from certain portions of the time tape data records, but the content of the spectrum tape power spectrum records is derived by Discrete Fourier Transform (DFT) and magnitude-squaring from the time-tape time series. IV. Description of Program Flowchart At the start of the program (Fig. 1), the table of values of the complex exponentials required by the DFT/FFT is computed. (See Sect. V for a discussion of the expo- nential table). Also computed at the start of program is a table of indirect address keys designed to manipulate any 256-point time series of normal sequential ordering into the so-called "shuffled" or "sorted" order required by the particular canonical form of FFT used. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 87 The program asks for input of date parameters required to be included in the spectrum tape output from the program. Also, in advance of each receive run to be processed, the program asks for the record serial number delimiting the last record of the run. The program tests for end-of-tape prior to reading each data record and calls for the next tape in sequence to be mounted. The core dump record, which is the first record written on each new reel of tape, is always skipped. Since the inte- gration of power spectra is always over all spectra com- puted in the course of a given receive run, the integration accumulator is cleared to zero prior to processing data for the run. The program's logic effectively makes the reading of successive records continuous in spite of the reel-to-reel transition, and does not "lose" any records either reel-to- reel or run-to-run. Processing of a given receive run terminates when a record of greater serial number than that for end-of-run is encountered. This record is retained and used as the first record of the next receive run. The requirement that only continuous, successive time-records be FFT'ed is enforced by checking the incrementation of record serial numbers and also checking the incremen- tation of the recorded time-of-day words on the suc- cessive records. Data from the time tapes are read in 256-record blocks in order to gather the time series to be transformed. Somewhat unfortunately, however, 256-point complex- valued time series are obtained for all 64 range gates at once. Since a total of 32,768 datd words are obtained, it was found necessary to use drum storage (RAD) to hold the full data set. The program, therefore, organizes the reading of a 256-record block as eight (8) 32-record blocks, and exploits the fact that each 32-record block (4096 words) conveniently fills one band of the drum, thereby tending to minimize drum loading time. The 4096-word record written to the drum band is derived by reading 32 records from tape to core memory in such a way that the 32 successive complex numbers for each range gate versus time are grouped contiguously. The data for each range gate are made available to the FFT computations by reading selectively from the 8 drum bands containing the total 256-record block and loading these data to a scratch pad area of core memory. The time-sequential order of the data is altered to the "shuf- fled" order used by the transform. A conventional com- plex FFT is done for each range-gate's data, with moni- toring of any computational overflows which may occur anywhere in the processing of the 32,768-word block. Since the first receive run of a given day's records is actually a delay calibration of the transmitter-receiver system, rather than a planetary return, the somewhat larger measurement values of the delay calibration are handled by right shifting all data 2 bits, with subsequent left shift correction in the computed results. The 256- point (512-word) complex-valued transform computed by the FFT for each range gate is magnitude-squared to produce a 256-word single-precision power spectrum for the gate. The power spectrum is accumulated in a double- precision accumulator assigned to each gate number. When all full 256-record blocks of the receive run have been processed (with any remaining number of records less than 256 being ignored), the integrated spectrum for each gate is normalized by left-shifting until the largest spectral element is scaled to maximum positive magni- tude. The number of shifts required for the maximum element is then applied to all elements of the spectrum, thereby yielding a normalized spectrum for the gate. The number of shifts required to normalize each spec- trum is incorporated into a computed scale factor, whereby the normalized spectrum can later be un-nor- malized, if desired, by the user. When processing of data for each receive run is fin- ished, the 65 records for the computed run are written on the output spectrum tape. The successive 65-record blocks comprise the output for each day's records. In the Mercury data processed, data for six days records appear on the spectrum tape. V. Doppler Interpretation of the Discrete Fourier Transform The following necessarily brief discussion is intended to address various user questions which have arisen in connection with the content and mathematical interpre- tation of doppler spectra generated by the present com- puter program. Suppose that a discrete time series of N complex-valued detector-output amplitude samples {Z;}, 0 < i < IV — 1, has been obtained at a uniform sampling rate. Suppose further that the discrete samples are actually samples of a continuous waveform representable as a sum of har- monics in the usual sense of Fourier analysis, in which the frequencies of the assumed harmonics are expressible as integer multiples of a lowest- or fundamental-frequency sinusoid. With IV discrete samples available, it is known that N harmonics are sufficient to fit the time series ex- actly. The N assumed harmonics comprise a dc (constant) JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 waveform, plus N — 1 sinusoids whose frequencies are integer multiples of a sinusoid having one period of oscil- lation in the time required to gather the N samples. In planetary radar, the amplitudes of all the harmonics are of interest, and these are computed by the Discrete Fourier Transform (DFT). The DFT is a computation which may be indicated by (but is not usually computed by) the following symmetric N X N matrix times N-vector multiplication: Si S.v-i 2* ZD z, N = dimension of transform 0 < n < N — 1 column index 0 < m < N — 1 row index /' = imaginary unit Recalling that the determination of the harmonic ampli- tudes in a conventional Fourier analysis involved multi- plication of the given time function by one of the as- sumed harmonic functions and integrating, it will be evi- dent that the DFT involves an analogous procedure. The analogue may be seen by examination of any of the row- times-column products in the multiplication: Each row of the DFT matrix is simply a tabulation of the complex exponential (sinusoid) for integer frequency m (row in- dex) versus time n (column index). Thus, the complex exponential for frequency m is being multiplied by the time series {Zj}, with summation (integration) of this product with respect to time to produce the harmonic amplitude sm for frequency m. This process, for a given row (frequency), will extract the value (Fourier amplitude coefficient) of one of the unknown amplitudes. If the time series {ZJ is assumed to be represented as a sum of harmonics •^ / 2:r \ Zm = 2_, cn exp l+j—nm 1 11 = 0 \ J / 0 ~ = exp| ~] '"w (nrnmod N) J and, more specifically, From the latter identity, for 0 < n,m < N, it may be seen that postulating high positive harmonic numbers, such as 255, is mathematically indistinguishable from postulating low negative harmonic numbers, such as —1. The completeness of the transform with respect to postu- lated frequency components at the harmonic numbers 0,1,---,(2V — 1) is retained if arbitrary (and possibly non- contiguous) harmonic numbers outside this range are postulated, provided that the set of the chosen harmonic numbers is congruent to 0,1,- • -,(N — 1) modulo N. Thus instead of postulating harmonic numbers 0,1,2,•••,255, it would be entirely equivalent, for example, to postulate that the frequencies +128, -127, -126,---,-l,0,l,2,---, 126,127 are contained in a 256-point -time series. For doppler amplitude samples obtained from planetary radar, for example, such a choice seems natural: on phys- ical grounds, it is known a priori that (a) the doppler re- turn does in fact contain frequency components above, below, and at the carrier frequency, and (b) all frequency components lie in the immediate neighborhood of the carrier frequency. Now, heterodyning of the doppler re- turn to dc (zero frequency) would be expected to produce positive- and negative-frequency components with re- spect to dc. Therefore, if the function of the DFT is to extract a spectrum of this form, the user is postulating a set of harmonic numbers such as +128, —127, —126,- • • , -1,0,1,2,-••,126,127 rather than any of the other choices he could have made congruent modulo 256. The burden of justifying an assignment of the spectrum values com- puted by the DFT to any postulated set of frequencies, then, necessarily rests with the user. The present computer program accommodates the + 128, -127, -126,••-,-1,0,1,2,-•-, 125,126,127 assign- ment by computing the DFT icithout regard to this assignment, and then permuting the order of the elements so as to reflect the user's view. The permutation may be indicated schematically as: from DFT So Si _ $255 _ to user Sl28 Sl29 $254 s, $2 Sl26 r frequency having no ± sense -*— most negative frequency dc _ •«— most positive frequency symmetrical frequency spectrum 90 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 With an even number of points assumed in the time series (256 in the present discussion) the + 128th har- monic number gives a waveform identical to that for the - 128th (+128 = -128 mod 256). Since only one of these could be computed (either, with the same computational result), there seems to be no meaningful interpretation of s12S as a doppler frequency amplitude component. Inter- pretation is not, however, a part of the computational requirements. Thus, s12S is computed for the sake of com- pleteness of the transform, and is furnished to the user along with the other spectral elements. Intentionally omitted from the foregoing discussion was elaboration of the fact that a power spectrum is the computational result furnished to the user. A power spec- trum is obtained from the amplitude spectrum (computed by DFT) by magnitude-squaring the elements, and sum- ming all spectra computed in successive 256-point blocks making up a given receive run. Thus, the user gets: z all trans- forms in a receive-run By the statistical stationarity assumed for the spectra of successive 256-point time series, the computed spectra are simply SNR-enhanced by the summation, i.e., an SNR-improved estimate of the doppler spectrum is ob- tained. The magnitude-squaring operation wipes out the phase information for each frequency component, and preserves only a power measure of each component. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 91 Table 1. Time tape record format and contents Time tape record format BOT marker Core dump record: 4096 words, dumped from memory loca- tions 0-409510. Table 2. Spectrum tape record format BOT Long erasure EOF Data record: 192 words Data record: 192 words • Data record: 192 words all data records formatted identically Header record Spectrum record, range 0 Spectrum record, range 1 . EOT marker Time tape 192-word data record contents Word No. (1-192) 1 2 3 4 63 64 j 65 66 67 68 • 127 128 129 130 131 132 191 192 Spectrum record, range 63 Header record Spectrum record, range 0 Spectrum record, range 1 . Record serial number (binary integer) Time of day in seconds ( binary integer ) Parameters Real sample } Imag sample j Real sample "1 Imag sample J Real sample "| Imag sample j Real sample | Imag sample ) Real sample 1 Imag sample j Real sample "> Imag sample j Range order of complex pairs GateO Gatel : 1 Gate 31 GateO Gatel Gate 31 1 / ° Coder 1 • } ^ 1 / l \ ) Coder 2 V 63 Spectrum record, range 63 Receive run 0 Receive run 1 Header record | Last receive Spectrum j run of day 1st Days records EOF EOF Header record Spectrum record, range 0 Spectrum record, range 1 • Spectrum record, range 63 Receive run 0 > Receive run 1 1 Last receive J run of day 6th Days EOF EOF (extra EOF) 92 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 3. Spectrum tape 197-word header record contents Word No. (1-197) 68 69 70 71 132 133 134 135 196 197 ID initially 00000000, increments 1000S after each receive run of day No. of words in record — 2, = 195]0, binary integer Record type = 5 if Run 0, otherwise = 4, binary integer Date record written (processed), 6-digit BCD packed in single 24-bit word, YYMMDD Date data taken (from radar log), 6-digit BCD, single 24-bit word, YYMMDD 64-word record, exact copy of time tape data record header, for the first time point of the first continuous 256-record time-tape data block successfully transformed in the receive run 64-word record, exact copy of time tape data record header, for the last time point of the last full continuous 256-record time-tape data block- successfully transformed in the receive run 63-word record, listing the record serial numbers of the first records of all of the full, continuous 256-record blocks whose power spectra con- tribute to the accumulation of spectra for the receive run. Table 4. Spectrum tape 262-word power spectrum record contents Word No. (1-262) 1 ID 1-word field has the 8-digit octal form rrrrrggg. Field rrrrr is initially zero; and increments by 1 after each receive run of day. Field ggg is the gate number for which the spectrum was com- puted. Field ggg is of the form abb: a = 1 or 2 (for Coder number 1 or 2, respectively), and bb is the gate number 0-316. No. of words in record-2, = 26010, binary integer Record type = 3, binary integer 7 8 9 135 261 262 Date record written (processed), 6-digit BCD packed in single 24-bit word, YYMMDD Date data taken (from radar log), 6-digit BCD packed in single 24-bit word, YYMMDD SF (scale factor). A positive binary integer giving the number of right shifts required, for all words in the power spectrum, to restore the absolute scaling of the spectrum. The absolute scaling is that which obtains when integer time series are Fourier-transformed using the conventional FFT (with factor 1/256 omitted), with squaring and accumulation of spectra for all 256-record blocks in a given receive run. Power spectrum point, frequency ±128 Power spectrum point, frequency —127 Power spectrum point, frequency —126 Power spectrum point, frequency 0 Power spectrum point, frequency +126 Power spectrum point, frequency +127 256-point power spectrum fora given range gate JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 93 $NEWDAY $NEWRUN REENTRY $RESET (REENTRY) $LP8 JLP32 LOAD FFT DATA TO FFT SCRATCH $5PECLP GO TO $RESET Fig. 1. Computer program flow chart 94 COMPUTE RAD ADRS UPDATE SPECTRUM RECORDS READ ONE SPECTRUM FROM RAD NORMALIZE, GET SCALE FACTOR GO TO $NEWRUN JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 14307 Radar Ranging of the Planet Mars at 8495 MHz G. S. Downs and P. E. Reichley Communications Systems Research Section A simulation was performed for the radar system in order to ensure detection of the planet Mars at the start of the 1975 series of radar probes of the surface. Appropriate parameters were found. Appropriate parameters were also found for use at opposition (December 1975). Systematic errors in the measured delay with changes in surface roughness were observed. This effect is shown to be many times larger than the expected rms fluctuations in the measured delays. \. Introduction The surface of the planet Mars will be probed with S- and X-band radar signals during 1975 and 1976, all in preparation for the landing of two spacecraft in 1976. The measurements to be performed at JPL will use the R & D radar system at DSS 14, Goldstone, California, at a frequency of 8495 MHz. In preparation, several series of radar data sets were simulated and processed. That is, the expected power in the reflected signal was calculated as a function of time delay and frequency for several sets of radar system parameters. The random fluctuations caused by receiver noise were superimposed using a random number generator. The appropriate signal-to- noise ratio was calculated for certain distances to the planet, assuming appropriate X-band antenna param- eters. The round-trip time delay of the signal reflected from the surface of the planet was determined. Up to 120 delay measurements were made to allow determination of the detection probability and the measurement accu- racy. An appropriate set of radar parameters was chosen in light of the results of this study. II. How Delay Is Measured The basic radar data set consists of a matrix of re- ceived power as a function of time delay and excess dop- pler shift. Separate regions on the surface will exhibit separate time delays because of the spherical shape of the planet. Let 9 represent the angle between the line of sight from the radar to the center of the planet and the radius to the JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 95 point on the surface. The time delay ^ of the signal re- flected from that surface point back to the radar is given by (1) where R is the radius of the planet and c is the speed of light; D is the distance along the line of sight to the closest point on the surface. Note that 6 is also the angle of incidence of the signal on the surface. 6 and D are each functions of time. The large delay due to D is re- moved at the time of data collection. The small changes in 6 due to the relative motion of Mars and Earth in the time interval 2D/c are neglected. The locus of a curve of a constant r is a circle in the plane perpendicular to the line of sight and whose center lies on the line of sight. Regions of a particular delay are isolated by modu- lating the phase of the transmitted signal with a pseudo- random binary code. If the bit length of the code is T seconds, the normalized cross correlation function of the transmitted signal with the received signal is given by RrM '• - -^ IT - T« I; -T0| T (2) where TO is the round trip delay. A band of surface ele- ments located within T seconds of TO can be isolated. In practice, the received signal is passed through a bank of correlators, the tth corresponding to a round trip delay T0 j . The power in the output of the ith correlator is then the sum of the power in the reflected signals correspond- ing to the delays r0i — T 6 is evidence of the decreasing peak amplitude. By includ- inly only the values of r for which nd < 6 in the statistics, a true representation of the measurement accuracy is obtained. Including all available values of T produces a larger variance because of the systematic drift in T with window position. The mean n,c is a function of the roughness parameter C. In Fig. 4(a) the measurements of T are presented vs nd for C = 150 at a distance of 0.56 AU. The drift in r with nd is not as extreme as in Fig. 3(a) since the back- scatter function varies more slowly with 6. Note however that TJ,C for nd < 6 is not identical to the similar value in Fig. 3(a). This bias is again caused by the retarded, flat- ter delay functions characteristic of low values of C or 98 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 larger values of 6. The data of Fig. 4(b), corresponding to D = 0.8 AU, show how small signal-to-noise ratios mask the effects discussed above. At opposition D = 0.56 AU. The results of Table 1 indicate that maximum ranging accuracies of 40 to 300 ns can be obtained. The systematic changes of T with nd and C are large compared to these hypothetical accuracies. It will then be desirable to apply corrections to the esti- mates of T to obtain the minimum possible rms fluctu- ations. The data of Tables 3-4 were obtained in a search of the data-frame parameters which ensure detection of the planet Mars at the start of the 1975 series of measure- ments (during August, when Mars is at 1.2 AU). The parameters underlying Table 4 (T = 12 ps, AL = 0.64 deg) provide a reasonable probability of detection of rough as well as smooth surfaces at 1.2 AU. These are the parameters to be used at the start of the series of mea- surements. Tables 2 and 3 are useful as an aid in deter- mining what T and AL should be as Mars progresses towards opposition. References 1. Hagfors, T., "Backscattering from an Undulating Surface with Applications to Radar Returns from the Moon;" }GR, 69, pp. 3779-3784,1964. 2. Hagfors, T., Radar Astronomy, Evans, J. V., and Hagfors, T., eds., Chapter 4, pp. 187-218, McGraw-Hill, New York, 1968. 3. Freiley, A. J., "DSS-14 XKR Cone Performance," JPL Interoffice Memo No. 3331-75-001, Mar. 10,1975 (an internal document). JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 99 Table 1. Detection probability and a- for T = 6 us, AL = 0.16 deg, p,( = 0.08 5, 0.56 50 150 300 1000 2000 5000 0.80 50 150 300 1000 2000 5000 1.00 50 150 300 1000 2000 5000 1.14 50 150 300 1000 2000 5000 r*% 98 100 100 100 100 100 56 97 100 100 100 100 3 62 83 95 95 92 2 38 73 86 91 88 P* % 1 0 0 0 0 0 10 0 0 0 0 0 57 1 1 0 0 0 50 10 3 0 0 0 ND 118 120 120 120 120 120 65 113 117 117 117 117 4 76 102 117 117 113 2 38 73 86 91 88 "TV T6o> /JS US 0.44 2.6 0.26 2.4 0.31 2.3 0.31 2.0 0.38 1.7 0.45 1.4 1.33 0.65 0.62 0.39 0.40 0.54 1.80 1.18 0.72 0.62 0.55 0.57 1.34 1.52 0.94 0.45 0.54 0.50 NO 64 64 64 64 56 56 40 61 61 61 55 55 _ 42 54 58 55 52 _ 29 39 50 52 49 "re, /tS 0.30 0.12 0.08 0.09 0.04 0.04 1.38 0.42 0.15 0.11 0.04 0.04 _ 0.98 0.57 0.33 0.32 0.22 — 1.44 0.80 0.38 0.45 0.35 rte> /*s 2.4 2.25 2.1 1.75 1.4 1.1 _ - - - - - _ - - - - — - - - - - 100 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 2. Detection probability and , = 0.08 D, AU 1.00 1.14 1.50 C 50 150 300 1000 2000 5000 50 150 300 1000 2000 5000 50 150 300 1000 2000 5000 % 12 81 82 93 94 93 4 60 82 93 94 93 _ - 30 76 83 84 P., _ 3 3 0 0 0 _ 6 3 0 0 0 _ - 10 0 0 0 *, 13 91 83 94 95 94 4 61 83 94 95 94 _ - 26 67 73 74 "TO' rbo> 1.47 1.09 2.5 0.81 2.5 0.61 2.0 0.49 1.6 0.74 1.5 1.15 1.50 0.81 0.61 0.49 0.74 _ _ - 1.37 0.53 0.63 0.45 "e 8 56 46 52 47 46 _ 34 46 52 47 46 _ - 20 41 37 37 /is 1.18 1.24 0.68 0.58 0.56 0.54 _ 1.50 0.68 0.58 0.56 0.54 _ - 1.28 0.59 0.65 0.51 Tic- IIS — 2.5 2.5 2.0 1.6 1.2 _ - - - - - _ - - - - - ORIGINAL PAGE is POOR QUALITY JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 101 Table 3. Detection probability and OT for T = 6 /is, AL = 0.64 deg, />„ = 0.08 D, AU 1.00 1.14 1.50 C 50 150 300 1000 2000 5000 50 150 300 1000 2000 5000 50 150 300 1000 2000 5000 %' 46 92 100 100 100 100 11 78 95 100 100 98 _ 9 49 78 80 84 %' 12 1 0 0 0 0 31 6 0 0 0 1 _ - 5 0 0 0 v. 49 98 106 106 106 106 10 74 90 95 94 93 _ 8 44 69 71 75 CTTO» T6o» /US JUS 1.92 3.3 0.93 2.7 1.00 2.7 0.91 2.2 0.61 1.7 0.67 1.4 1.60 1.50 1.00 0.75 0.64 0.71 _ _ 1.5 1.62 0.72 0.47 0.64 », 31 65 70 70 53 53 6 48 57 62 49 50 _ 7 27 44 37 37 "re- ps 1.72 0.98 0.65 0.51 0.29 0.20 2.0 1.55 0.84 0.53 0.56 0.82 _ 1.40 1.20 0.65 0.46 0.25 Tbc> MS 3.1 2.9 2.6 2.0 1.5 1.1 _ - - - - - _ - - - - - 102 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 4. Detection probability and REU •C 3 i <-> IMU = 0-H-ZERO = 0 -1 (real unit), (imaginary unit), II. Scalars The complex number system can be simulated by a class of 2 by '2 matrices. The identification is: Z*W = If 2 <-» Z and .u; <-» W, then z «-» TRNfZJ and z + w «-» Z+W. Also, zw «-> Z*W, for if z=a + ifo, u; = c+td, then ztv = ac — bd + i(ad + foe), -b ~ |_ad+foc —ad—bc ac '-fo i -bd] • JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 115 If z=£0, thenl/z <-» 1KV(Z), ic/z <-> W*IKV(Z). which can be constructed by a declaration: The squared magnitude \z\- can be obtained as a scalar real by calling DET(Z), or as a complex real by using: o Example: A digital filter has the z-transform transfer function h(z) = 1 + 1-z The following MBASIC program prints \h(e''"')\2 vs f for / = 0, 0.05, 0.1, • • • ,0 .5 Hz: >LIST 10 REAL REU(2,2)/IDN(2)/, IMU(2,2)/0,-1,1,0/, Z(2,2) H(2,2) 20 PRINT 'HZYRESPONSE' \ HZ, DET(H) WHERE HZ = K/20, OMEGA =2*PI*HZ, Z=COSR(OMEGA) *REU + SINR(OMEGA)*IMU, H = REU + ((REU -Z)*INV(2*Z-REU))**3 FOR K=0 TO 10 >RUN HZ 0 .5E-01 .1 .15 .2 .25 .3 .35 .4 .45 .5 RESPONSE 1 1.0460479 1.1580165 1.087936 .92637333 .776 .66241923 .58356814 .53269148 .50431055 .49519892 >REAL M = 2, N = 3, A(M,N)/1,2,3,4,5,67, B(M,N)/7, & 8,9,10,11,12/ >REAL El(2*N,M)/TRN(A),TRN(-B)/,& E2(2*N,M)/TRN(B),TRN(A)/,& E(2*M,2*N)/TRN(E1),TRN(E2)7 > PRINT USING '(6(4%)/)': E 1 2 3 - 7 - 8 - 9 4 5 6 - 1 0 - 1 1 - 1 2 7 8 9 1 2 3 10 11 12 4 5 6 Similarly, A and B can be reconstructed from E: >REAL ZERO(N,N), REPT(2*N,N)/IDN(N)/,& IMPT(2*N,N)/ZERO, - IDN(N)/ >REAL E3(M,2*N)/E/, A(M,N)/E3*REPT/,& B(M,N)/E3*IMPT/ > PRINT A:\\B: 1 2 3 4 5 6 '7 8 9 10 11 12 Complex matrices can be added and multiplied (if con- formable) by doing the operations on their E-matrices. In particular, a nonsingular n-by-n complex matrix can be inverted by using the function INV on its E-matrix. We can also associate a complex n-vector X + iY with the column vector Then the multiplication (A+iB)(X + iY) can be executed by performing III. Matrices A powerful extension of the technique allows arithmetic with complex matrices without resorting to subscript manipulation. With the complex m-by-n matrix A+iB, associate the real partitioned 2m by 2n matrix E = B A -B B A 1\~X~\ TAX-BY-] JL Y J ~LBX+AYJ Example. The following MBASIC program solves com- plex n-by-n linear systems AX = B. It is run with the example ri+n = 0 116 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 >LIST 10 INPUT USING 'DIMENSION: #':N 20 REAL AR(N,N), AI(N,N), BR(N), BI(N) 30 PRINT 'INPUT REAL PART OF A, THEN IMAG- INARY PART 40 INPUT AR,AI 50 PRINT 'INPUT REAL PART OF B, THEN IMAG- INARY PART 60 INPUT BR,BI 70 REAL A1(2*N,N)/TRN(AR),TRN(-AI)/, A2(2*N,N)/TRN(AI),TRN(AR)/, A(2*N,2*N)/TRN(A1),TRN(A2)/, B(2*N)/BR,BI/, X(2*N)/INV(A)*B/ 80 PRINT 'REAL PART OF SOLUTION' \ X(K); FOR K=l TO N \\ IMAGINARY PART OF SOLU- TION' \X(K); FOR K = N + 1 TO 2*N >RUN DIMENSION: 2 INPUT REAL PART OF A, THEN IMAGINARY PART INPUT REAL PART OF B, THEN IMAGINARY PART REAL PART OF SOLUTION -.49999998 .5 IMAGINARY PART OF SOLUTION .49999999 -1.5 It is also possible, though perhaps not as convenient, to associate the m-by-n complex matrix (aik + ibj*) with the real 2m-by-2n matrix F = zml .z. where Zjk is the 2-by-2 matrix we were associating with the complex number aik + ibjk. These F-matrices can be manipulated just like the E-matrices. One can go from one to the other by row and column permutations. In this connection, we mention that DETfEj = DETfFj = \det (A+iB)|2 . Is there a way to compute det(A-HB) in the same spirit? R. J. Hanson showed that if A + tB is Hermitian, then its E matrix has the same eigenvalues, with the multiplicities doubled (Ref. 1). L. W. Ehrlich (Ref. 2) showed that inversion of A + t'B with complex arithmetic can be car- ried out faster and more accurately than inversion of E with real arithmetic. Of course, if the complex inversion has to be coded step by step in the source language of an interpretive processor, it cannot compete in speed with real inversion of E by a machine-language subroutine. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 117 References 1. Hanson, R. ]., Remarks on the Calculation of Eigenvalues and Eigenvectors for Complex Hermitian Matrices, Technical Memorandum 205, Jet Propulsion Laboratory, Pasadena, Calif., October, 1968. 2. Ehrlich, L. W., "Complex matrix inversion versus real," Communications of the ACM, Vol. 13, pp. 561-62,1970. 118 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 DSN Standard Practices for Software Implementation D. C. Preska TDA Planning Office DSN Standard Practices for implementing software are being applied to all new computer programs and modifications to be transferred to DSN Operations. This article presents an overview of the DSN methodology and prescribed practices. The methodology is based on established good engineering practices combined with newer software technologies involving structured programming, top-down principles, and concurrent construction and documentation. The practices provide the DSN with a means of producing maintainable software which is correct, on schedule, and within cost limitations. The ultimate goal is to permit DSN engineers and managers to concentrate their efforts not on details of machines and languages but rather on the tracking and data acquisition problem to be solved. I. Introduction To more effectively produce software, elements of the DSN Programming System have been defined to allow refinement and application of new methods in an orderly manner. The ultimate goal is to permit DSN engineers and managers to concentrate their efforts not on details of machines and languages but rather on the tracking and data acquisition problem to be solved. The DSN Programming System includes (1) implementation method- ology, (2) Standard Practices for applying adopted methods, (3) language and data base standards, and (4) implementation aids. In conjunction with the Program- ming System, a DSN Software Management Seminar with wide participation was established and several pilot software implementation projects were undertaken. This report presents an overview of the Standard Practices (Ref. 1) developed from both the methodology research and continuous input from the Software Management Seminar. The prescribed methodology combines proven, well- established engineering practices with emerging tech- niques that are mathematically sound and have been demonstrated by many independent workers involved in software development The elements of the methodology and the management practices involved in their applica- tion are discussed, followed by a set of brief statements JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 119 that sum up the essence of the Standard Practices for software implementation. II. Methodology The methodology used for implementing DSN opera- tional software makes use of the theorems of structured programming and its consequent enabling of top-down construction of programs. Application of structured programming and top-down practices further allows design and documentation to be performed concurrently with the coding and correctness testing in orderly, hierarchical builds. These terms will be defined below. The elements of the methodology are: (1) Principles of Structured Programming (2) Top-Down Construction (3) Concurrent Design and Documentation, Coding, and Testing A. Principles of Structured Programming Structured programming is a program organizing and implementing technique that involves the concept of representing the control logic of arbitrary computer programs with iterations of a limited set of primary program (or flowchart) structures. The objectives of structured programming are increased clarity, increased commonality (interchangeability/module-to-module, pro- gram-to-program, project-to-project), reduced complexity, and simplified maintenance. Also, structured programming allows the top-level main program control to be designed and documented while leaving the lower levels of detailed computational design to be rigorously designed later. The Structured Programming Theorem states that any program, arbitrarily large and complex, can be expressed by primary structures that need include only the operations for performing (a) functional sequencing, (b) conditional branching, and (c) conditional iteration (looping). Application of the concept of iterating only a small number of standard structures results in a highly organized and structured representation of the design and subsequent code that is easy to implement, read, test, and understand. Coding of the design by using prescribed primary code structures is referred to as "structured coding" which typically also encompasses code indenta- tion and line spacing to display the program flow and modularity clearly to persons reading the code. The ease with which the primary structures can be translated into code depends upon the characteristics of the programming language. To facilitate this translation, the DSN intends to adopt the language MBASIC as its standard for nonreal-time programs. The main advantage to a DSN standard language, however, is the full portability of DSN applications programs from one machine to another. Limiting the complexity of a flowchart enhances its clarity and readability. This can be achieved by using the "striped module" technique (Ref. 2) to indicate that further detail is provided elsewhere. Unstriped modules contain sufficient detail to be translated directly into code. B. Top-Down Construction The top-down approach involves the concept of stating the total problem in its operational environment and progressing in a systematic manner to greater levels of detail. This provides the capability for engineers and managers to fully understand the problem and to define a solution (a proposed program) based on this understanding. The early stages of this program-defining process are characterized by iteration and nearly parallel thought processes, of which most, ideally, should have been completed in advance of the formal implementation. An orderly, more serial process of program production or construction follows, and includes: final detail design, translation of this design to code, auditing and testing the code, and documentation of the design, code, and test processes. The top-down procedure for this construction process is referred to as top-down construction. Top-down construction is especially adapted to struc- tured programming because the Structure Theorem allows the top levels to be constructed first and then the lower levels to be detailed (unstriped) and constructed in an orderly and rigorous fashion. Specifically, in terms of detailing and flowcharting in preparation for construction, one starts with a single striped module (level zero). That module is analyzed and expanded into a flowchart with two or more modules. The structure of the flowchart must be either a prescribed structure or a permitted combina- tion of prescribed structures where any or all of the modules may be striped. Each striped module at this point (level 1) is expanded into a flowchart in the same way. The modules which are not striped need not be expanded and this means that they can be directly translated into code without further design. This process is repeated at the next level and continued until there are no striped modules which have not been expanded. The expansion can be completed in some paths before it is completed or even started in others. External interfaces are defined, negotiated, and imple- mented early, and then used in the subsequent develop- 120 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 ment. This minimizes the occurrence of possible serious program integration problems after the internal develop- ment has been completed. Also, the need for developing program "drivers" is reduced or eliminated. This progres- sion of the implementation from the interfaces into the detailed program computations is consistent with the theory of computable functions, which requires that at any point of computation all elements needed to compute the next value have already been computed. The top-down approach is also a valuable management tool, in that the resulting end-to-end overall definition of the proposed program and its component parts and structure provide program design guides and data needed for estimating the scope of the total job, for determining the nature of the work and needed resources, for planning and scheduling work through the various phases, and for managing and conducting design reviews. C. Concurrent Design and Documentation, Coding, and Testing Concurrent activities of design and documentation, along with coding and testing in hierarchical builds (module-by-module program expansions, each increasing in lower level detail) are enhanced by the use of structured programming and top-down practices. Timely documentation, resulting from use of these practices, provides ready access to current program detail and status. Management of the effort and provision for Quality Assurance are both facilitated. Potential problem areas can be identified early for timely action. Also, a large-scale separate documentation effort at the end of the project, with its attendant problems, is avoided. In terms of coding and testing, any unstriped module can be coded as soon as the flowchart on which it appears has been completed and signed off. Moreover, the program can be run provided any striped modules are properly represented by modules of temporary code called dummy stubs (code which produces data values which are needed to run the rest of the program along other paths). The dummy stubs are intended to work for one or more special test cases. There is a correctness theorem in Structured Programming which says that if the part already coded is proven to be correct, then it will still be correct after the rest of the program is coded, and thus need not be checked again. The test cases verify, build-by- build, the correctness of the module when imbedded in higher builds of code by testing every module-connecting path and by performing other tests as needed to uncover, for example, errors in logic, computation, formatting, timing, recovery, and documentation. Correcting errors as they are introduced minimizes rework and avoids later serious impacts due to compounding of errors. It can therefore be expected that the total amount of testing (correctness and acceptance) will be greatly reduced, since, at completion of coding, there is no need to repeat extensive internal program (correctness) testing; the program is correct. Needed are only those tests (accept- ance) that demonstrate to the user the program's responsiveness to requirements in its full operational environment. Figure 1 represents the process followed in doing concurrent design and documentation, coding, and testing from the top down. The figure shows that the module design as documented must be approved before the module coding and correctness test design are begun, both of which must, in turn, be completed and checked before the correctness testing is performed. However, after design approval, the test is designed at the same time as the coding is being done. Testing, and approval of the results of the test and code audit, formally completes the build at this level. Symbols for scheduling as shown are provided for planning and monitoring the implementation progress within each build. III. Management The methodology enables effective application and management of the practices and concepts, and also enables effective team operations for large efforts. The DSN software implementation process extends from an initial program justification activity through program transfer to operations and involves (1) planning and specifying requirements, (2) design definition, (3) design and production, (4) acceptance, and (5) operations and maintenance. Major milestones are defined mainly at the end of each phase of activity, above. Figure 2 presents an overview of a typical DSN software implementation sequence, and Figure 3 summarizes the DSN software management and implementation plan, as derived from Fig. 2. The figures are self-explanatory; however, further description of the management and implementation activities can be found in Ref. 1. Supporting DSN Standard Practices shown in Fig. 3 are being produced. The implementation process using the prescribed methods is flexible and can accommodate both large and small efforts. For large efforts, an implementation team can be established, which is directed by a Cognizant Development Engineer (CDE) who is responsible for the implementation. The CDE is provided with functional support as shown in Fig. 4, such as (but not limited to): a Programming Secretariat for administrative assistance, JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 121 project communications, and data handling; Quality Assurance services; and technical specialist support as required, spanning the disciplines of design, coding, and test design, conduct, and evaluation. The functional tasks are independent but are not necessarily related on a one- to-one basis to team personnel. The Programming Secretariat maintains the project's development records, controls the completed code, and serves as the center of communications for the entire team. Specialists, as required, are functionally separated but work as a team on a module-by-module basis and provide needed expertise to the implementation, as well as providing, to a degree, "checks and balances" to the total process. Quality Assurance provides independent code auditing services to the team on a module-by-module basis. Reference 1 provides additional detail on these and other functional tasks involved, their interaction, and a functional task statement of responsibilities for each. Smaller efforts may require that the functional tasks be spread among fewer available personnel, which tends to lessen both the independence of each task and the inherent self-checking of the implementation process. This can be partially compensated for during the design reviews, where independent views can be factored in. Also, as for large efforts, independent code auditing on a module-by-module basis is required, and provides some of the checking needed. IV. Summary The following brief statements summarize the baseline software implementation guidelines that are applicable to DSN operational programs. Further comments, explana- tions, and examples of their application can be found in Ref. 1. Figure 5 displays the Table of Contents of Ref. 1 to show the overall organization of information upon which these guidelines are based (1) Adherence to DSN Software Standard Practices. DSN Standard Practices governing software imple- mentation and documentation are to be followed for all computer programs to be transferred to opera- tions. (2) Adherence to Referenced Practices. Referenced practices, standards, and requirements are consid- ered to be part of the DSN Standard Practices and are to be followed as an extension of Item (1), above. (3) MBASIC/Standard Language for Nonreal-Time DSN Computer Programs. It is the intent of the DSN to use MBASIC as the standard language for nonreal-time DSN computer programs. (4) Top-Down Concurrent Implementation. Software will be implemented in a top-down manner to allow the design and documentation as well as coding of the program to progress concurrently with the generation of correctness test procedures and the correctness testing itself. (5) Use of Structured Programming Principles. Only prescribed programming structures will be used for flowcharting the design and translating the design into computer code. (6) Modular Implementation. By applying Items (4) and (5), modules will be implemented in hierarchical subordinating levels of detail. Each module will be limited in length and complexity to a single page- size (81/2 X 11-in. (22 X 28-cm)) flowchart by using the Striped Module technique of hierarchical expansion. (7) Implementation Team. For sufficiently large pro- jects, the Cognizant Development Engineer will establish and direct an implementation team that is supported by the following main functions: (a) Programming Secretariat (b) Quality Assurance (c) Design, coding, test design, and testing special- ties, as needed (8) Standard Project Milestones. Standard project milestones will be used for technical and manage- ment planning and control of the software imple- mentation. (9) Project Scheduling. Schedules for meeting the project milestones will be established and periodi- cally assessed by the Cognizant Development Engineer and controlled by the cognizant manager. (10) Project Reviews. During the planning phase, dates will be set for all formal design reviews; the Cognizant Development Engineer will coordinate and conduct the reviews. (11) Project Documentation. Documentation will be compiled concurrently with the implementation progress and will be available on a continuous basis for use and review. (12) Quality Assurance. Quality Assurance (QA) will provide an independent check on DSN software quality. 122 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Acknowledgment The author is indebted to the members of the DSN Software Management Seminar, whose support emanated from JPL Organizations 15, 33, 39, 65, and 91, as well as from the DSN itself. References 1. Software Implementation Guidelines and Practices, DSN Standard Practice 810-13, Aug. 15, 1975 (JPL internal document). 2. Tausworthe, R. C., Standardized Development of Computer Software, Jet Propulsion Laboratory, Pasadena, Calif, (in preparation). JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 123 SCHEDULING SYMBOLS FOR BUILD N MILESTONES D _y OR D DESIGN APPROVED DESIGN LOGIC AND DOCUMENT TEST CODE; AUDIT; REPORT RESULT YEST CO£E_TESTING _COMPLE_TED 7 OR T TESTED Fig. 1. Top-down, concurrent construction process for Build N 124 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 PRIMARY RESPONSIBILITY FOR ACTIVITIES ACTIVITIES INITIATOR' I COE 1 CSE PI AMU 1 Kir. ^_^ SOFTWARE REQUIREMENTS DOCUMENT ARCHITECTURAL DESIGN .. SOFTWARE DEFINITION DOCUMENT DESIGN AND PRODUCTION SOFT WARE OPERATOR'S MANUAL AND SPECIFICATION DOCUMENT ACCEPTANCE TESTING TEST AND TRANSFER DOCUMENT OPERATIONS AND MAINTENANCE DURATION OF THE IMPLEMENTATION PROJECT... . 4 ' ( MANAGEMENT APPROVAL f TO PREPARE SDD) j (MANAGEMENT APPROVAL • TO IMP! FMFWT HF^IftKI 1 ^ . ii • PREPARE A TEST , 1 ., 1 1 1 *TYPICALLY, DSN SYSTEMS ENGINEERING (DATA SYSTEM S /W) ;OR OTHERS THROUGHOUT DSN DESIGN REVIEWS A MANDATORY A OPTIONAL Fig. 2. Sequence of activities in a typical DSN software implementation project JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 125 — — r-r-^H a o Z z o S * t1 £2" " £OT " ui S Z yse * *S 5 5 S^ I _L _i_ . _ n .^ - o Qo - Q O - O3 SlE 19 ITo z o O < u U S l l £ | I I l l O5 z og o Z 7 i^ p £ < S 2 o 5 P < " |S,r(2n - 1) ( 0 (4) neven and 08/2jr of 174 kHz. A straight line must be drawn intersecting the curve at this frequency to form the reference for measurement of 6ln and 0£, n = 1, • • •, N. The line should be drawn to cor- respond to the delay introduced by the subcarrier demod- ulator assembly subcarrier tracking loop. Since this delay will vary in a complicated way depending on the specific phase distortion, only an approximate lower bound to the degradation in signal power will be attempted. This can be done by adjusting the slope-of the line intersecting the curve at foa until the degradation appears, to be mini- mized. The values of 0% an(j 0vfOI n = 1, 3, 5 (even har- monics are absent anyway) are given in Table 1, using straight line references A, B, and C. Substituting the values of Table 1 into (9) yields pA = -0.48 dB PB = -0.45 dB c = -0.45 dB (12) where pA is the degradation using reference line A, etc. Actual measurements at CTA 21 yielded a downconverter/ upconverter degradation of 0.7 dB. Acknowledgment The author is indebted to S. Kent for the general approach used in this analysis as well as for numerous extremely helpful discussions. 138 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 1. 0 (1) where a and b are positive parameters characteristic of the month. Thus, for the ith month (» = ! , • • • , 12), two JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 141 parameters, a, and b\, are to be determined. This form of distribution has been found to provide good fits for the available data sets. The data base consisted of the following three groups of wind speed records: Set A B C Location Goldstone, Mars site Edwards AFB Edwards AFB Anemom- eter height, ft 150 13 13 Period of record, yr/mo to yr/mo 66/11-68/10 66/11-68/10 57/1 -70/12 No. of entries 9100 17,500 122,700 The Goldstone data consisted of average wind speeds for 5-min periods. The sampling rate was hourly except for December 1966 through August 1967, when the rate was 1 every 3 hours. Considering the number of observations that could have been made at these two sampling rates during the entire period, it has been found that about 25% of the data is missing. Sets B and C (Edwards data) were extracted from United States Weather Bureau archive tapes (by Meteorology Research Corporation at our request) and are complete sets of hourly records with no entries missing. Set B is actually a subset of C and was assembled for comparison with contemporary Goldstone data. Since the actual data for Goldstone, set A, covers a period of less than two years, it is not necessarily a reli- able basis for the desired probability models. As a means of assuring that the models represent long-term Goldstone phenomena, the following steps were taken, incorporating data sets B and C into the analysis: (1) Using a chi-square criterion for goodness of fit, 12 sets (QJ, foj) of monthly parameters were chosen based on the A data. (2) Using data sets A and B, the degree of correlation between monthly wind power (= speed3) at Gold- stone and Edwards was estimated. (3) Based on the results of step 2, the long-term data set C from Edwards was used together with A and B to obtain "corrections" of the parameter values found in step 1, the corrected values being designed to incorporate the long-term information provided by set C. II. Computation Methods A. Procedure 1 — Generation of Sample from the Dis- tribution of Eq.(1) A simulated monthly sample of wind speeds s, sample size N (1 per hour), can be constructed from a given dis- tribution by drawing «i = uniform (0,1) » = 1,2, • • •, N (28 X 24 < N < 31 X 24) and letting sj = F-'(«i) where F-1 is the inverse distribution function. Using the inverse function of Eq. (1) will provide Si = (a2 - - a where c = ln(uj) If desired, variance of the samples so constructed can be reduced by dividing the range (0,1) into p strata and drawing N/p uniform numbers for each stratum, then finding the inverse functions of these numbers as before. The variance of the sample can be made to approach zero by letting p approach N. When p equals N, the sample is no longer a random simulation, but instead tends to replicate the generating distribution. Note that when stratified, the samples will occur as p ordered clusters of N/p numbers. This ordering can readily be removed later by random scrambling of the sample. B. Procedure 2 — Long-Term Distribution Function Parameters (Steps 1-3, Section I) 1. Step 1. Prior to the present requirement, field data from Goldstone and other weather stations had been processed by a moderate-size computer program WINDMAPW. This consisted of about 1000 source card images plus references to several JPL 1108 FORTRAN V library and IMSL library subroutines for analysis and plotting. After reading the field data from tapes or files, one of the operations of the program was to fit Pearson and Weibull distributions to the data. For the current requirement, the Weibull fit was dropped and fitting methods for the function of Eq. (1), as will be described, were substituted. With these changes, this version of the 142 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 program was renamed WINDMAPW. The program cur- rently resides in a catalogued file (52219RIL) on the 1108A computer. Fitting parameters to empirical data was performed in two substeps. A preliminary regression analysis step was executed to provide class boundaries and starting points for a final chi-square calculation step. a. Preliminary regression estimate for parameters a and b of a sample. By taking the logarithm of both sides of Eq. (1) and rearranging, we have (a + bs) = - Then let Yj = a + bs, be the model equation for regres- sion analysis of Y on s, and let Si be the observed values of Yj, where F(s/) is the empirical distribution function of S. The regression is performed in a subroutine FITEXP. The input to this subroutine is (1) Sample = S(7), 7 = l,NT where NT = total number of terms in sample and S has been sorted in ascending order. (2) XMIN, XMAX, = lower and upper threshold speeds that bound the speed region of interest. The values used were 8 and 40 km/h (5 and 25 mi/h) based on typical low-speed threshold and high- speed generator capacity level, respectively. This subroutine performs the following operations: (1) Find IBOT, ITOP, indices of S such that S(IBOT) > XMIN S(ITOP) < XMAX (2) Perform regression on S(7) (IBOT < I < ITOP), using the following algorithm: (a) FX = I/(NT + 1) = empirical distribution (b) X = S(7) (c) Y = -ln(l - FX)/X (d) SY = 2 Y SX =ZX SXY = 2 XY SXX = 2 X' Then: NET = ITOP -IBOT + 1 DET = NET*SXX - SX*SX The resulting initial estimates for a and b are: a = (SXX*SY - SX*SXY)/DET b = (NET*SXY - SX*SY)/DET b. Final chi-square calculation estimate for parameters a, b of a sample. Divide the speed range between XMIN and XMAX into 8 interior classes and add one class at the low end to include all speeds below XMIN and one class at the high end to include all speeds above XMAX. Let Oj = observed number of speeds in class "i" (froni the empirical sample) Ei = expected number in class "i" Let Bi = lower speed class boundary for class "i"; then E; = NT * [F(B, + 1) - F(B,)] where F(.) is found by evaluating Eq. (1) using the current estimates of a and b. Let FVNCT(a,b) = S (0, - E4)V£i i = 1,2, •••,!() (2) The estimate of a and b is made by choosing a, b to minimize the function in Eq. (2). The operations are performed by subroutines FITEX1 and CHIPAM. F7TEXP (1) After regression has been performed to obtain the preliminary estimate of a, b, classes are set up for the calculation of FUNCT (Eq. 2) as follows: Let NCHI = number of interior classes between XMAX and XM7A7 (typically 8). Using Eq. (1) com- pute the difference in distribution function be- tween XMAX and XMIN. This difference is di- vided into NCHI parts, each part representing an equal probability of occurrence. Beginning with JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 143 F(XMIN) and adding these part differences suc- cessively is equivalent to evaluating the current distribution function at the interior class bound- aries. Consequently, evaluation of the inverse dis- tribution function (see Eq. 1) furnishes the class boundaries. At this point, these classes have been established so that E, = Ef for all the i, j interior classes. However, as the estimates of a and b change from minimization of Eq. (2), the equality is not maintained because class boundaries are not re- computed. (2) The number of terms in each of these classes is computed (O f ) (3) Calls subroutine CHIPAM. CHIPAM CHIPAM calls a JPL library subroutine to perform a conjugate direction search to find a and b that minimize Eq. (2). The search is performed by means of many (50 to 100) evaluations of the function in Eq. (2). At each evalu- ation, the EJ are computed using the current values of a and b. The search terminates based upon tolerance tests of 1 X 10-3 for a, 1 X 10-4 for b, and 1 X 10"3 on the func- tion. This last tolerance is equivalent to a very small frac- tion of the actual function (one part in 10,000 to 70,000). As a comment on the method of obtaining the final chi-square estimate of the parameters, we find no great changes from the preliminary parameters or function values obtained by regression. 2. Step 2. The correlation between data sets A and B was analyzed in terms of wind power P/, defined as a summation of min[S,25]3 (=min[S3,253]), where S = wind speed in miles per hour. The computational equa- tion is included in Table 1, and the computed values of PI for each monthly record in sets A and B are given in columns 1 and 4 of Table 1 (Goldstone) and column 5 of Table 2 (Edwards). It is assumed that the true correlation p between total power at Goldstone and Edwards in contemporary months is chronologically in- variant. It is also assumed that the pair (Goldstone monthly power, Edwards monthly power) has a specific distribution for each calendar month, so that for any specified month the result for any given year is an inde- pendent sample from this distribution. It follows from these assumptions that p is also the (true) correlation of the pairs of differences, which are defined as follows: (Gn -Gs.-.E,, -£.,),* = 1, • • • ,12 where Glt and G2i represent Goldstone power in the ith month of year 1 and year 2, respectively, and £,,- and E2i are defined correspondingly for Edwards. Because of missing September and October data at Goldstone, Tables 1 and 2 provide only 10 values of i where data from two years are available. These were used to estimate P by computation of the sample correlation coefficient of these 10 pairs, yielding the estimate: P = 0.486 This correlation coefficient appears to be sufficiently large to confirm that the approach outlined is reasonable; e.g., there is a statistical connection between the random deviations from monthly norms at the two locations, Goldstone and Edwards. For the analysis that will be described in step 3 below, it is necessary also to estimate the ratio of the standard deviations of G, and E,, which are the monthly powers for the ith month. This ratio is assumed to be independent of i and was estimated by the ratio of the two sample standard deviations that are determined for the 10 values of G,J — G2i and for the 10 values of EH — E2i. The result was the estimate R = an/aE = 953/664 = 1.44 3. Step 3. To determine "corrected" (a- t, bt) pairs, it is necessary first to utilize the correlation information in a rational way. The approach adopted was the following: (1) Estimate the long-term average of the Goldstone total power for the tth month, for i = 1, • • •, 12. (2) Use the results of (1) to correct the values of a, and bi obtained by the chi-square fit in step 1. To obtain the long-term Goldstone power for i = gi = true mean total power for the ith month (Gold- stone) Ai = average of G, ( and G2j (data set A, Table 1, Col. 4) B; = average of Eu and E2i (data set B, Table 2, Col. 6) C; = average of EH, • • •, E14i (data set C, 14 years, Table 2, Col. 7) (For September and October, Ai and B; were based on only one months' record, not two.) The estimate used for gf was , -B,) (3) 144 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 The values of A-,, B,, C, and g, are shown in columns 4, 2, 3, and 5, respectively, in Table 3. By the results of step 2, P R = 0.486 X 1.44 = 0.7 Equation (3) defines the appropriate "least weighted squares" estimator of g, in terms of the available data, A-,, BJ, and C,, as shown in the Appendix. This interpreta- tion depends on the correlation p and the standard devia- tion ratio R being known. Using estimates instead, as we have done, is natural and reasonable. More exact analysis is not feasible without knowledge of the form of the joint density functions describing wind at Goldstone and Edwards. Note that the effect of Eq. (3) is to correct the direct estimate A; of Goldstone wind power by adjusting for the difference between Edwards short-term power in the contemporary period and long-term power. For example, January data at Edwards (Table 2) shows B, slightly less than C, (i.e., 1045 < 1101), indicating that the short-term wind was slightly below the long-term average and sug- gesting a positive correction (increase) in the estimate of Goldstone wind power for January. Columns 4 and 5 of Table 3 show the estimated power before (2856) and after (2895) the correction was applied. Having the estimates g, of Goldstone wind power for the long term, it is necessary now to use these to correct the a, and fo, previously obtained. To clarify the method, it is helpful to rewrite Eq. (1) in the form where c = a/b and d = a-/b. Written this way, the family of distribution functions is seen to have a "scale factor" parameter c and a "shape" parameter d. For example, doubling all the wind speeds has the effect of doubling c, leaving d unchanged. On the other hand, if c is held fixed while d is changed, the "shape" changes. The shape effect is that, for very large d, the distribution is close to an exponential distribution, whereas for smaller d, it has thinner tails that are more like those of a normal distribution. The choice of a distribution to represent the fth month at Goldstone was made as follows: Let d, = a,2/bi (esti- mated in step 1) and determine c$ so that the average total power agrees with the value g, estimated in (1). Thus, a model is chosen which predicts total power in accord with the estimate previously derived and, among all sets of parameters satisfying this restriction, the choice is made to yield the same "shape" as was estimated di- rectly in step 1. Letting a,-* and b,* denote the parameters of the final distribution chosen for the ith month, F(s) = l-exp \-d - + (- b* = b,/ct\ which are shown in columns 7 and 8 of Table 3. The values of the c,'s are shown in column 6. Note that most of the c's are close to 1, indicating that the corrections made are small and that the short-term Goldstone data are, on the evidence of sets A, B, and C, likely to be repre- sentative of the long-term wind parameters at Goldstone. Figure 1 shows a diagrammatic summary of the logic underlying the generation of the wind speed samples. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 145 Table 1. Fitting parameters and power terms Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year 67 68 67 68 67 68 67 68 67 68 67 68 67 68 67 68 68 68 66 67 66 67 From observations on individual months a b P! 0.019700 0.085847 0.028782 0.1093.35 0.013132 0.047229 0.007951 0.030524 0.021088 0.044651 0.026241 0.022351 0.000001 0.004859 0.058394 0.030681 0.070572 0.144353 0.076671 0.132794 0.106911 0.068373 0.000268 0.001345 0.002222 0.002781 0.002406 0.00133 0.003035 0.002258 0.002853 0.003081 0.003175 0.004697 . 0.006994 0.006800 0.005100 0.005051 0.003518 0.000544 0.000677 0.000640 0.000412 0.000811 3695 2017 3028 1194 5230 3285 5347 4255 3966 3598 2986 3329 2097 1758 1475 2275 1681 1088 2265 1341 3090 3631 e (1) From data pools within corresponding months Year a b P, 67, 68 0.08927 67,68 0.100611 67, 68 0.048574 67, 68 0.025546 67,68 0.034341 67, 68 0.023422 67, 68 0.003654 67,68 0.043111 66, 67 0.102385 66, 67 0.074673 • (2) 0.000765 2570 0.002506 1476 0.001700 3872 0.002326 4530 0.002600 3722 0.003705 3248 0.006917 1907 0.004707 1981 0.001346 1933 0.000618 3489 • (3) Average 2856 2111 4258 4801 3782 3158 1928 1875 1681 1088 1803 3365 • (4) "Indicates that data in the column above was used in either correlation coefficient computation or in long-term Goldstone projection. Pf = f min(S\ 253)p(s)ds =± 5 min(C3., 25») p(C.) AC where Cj = class mark AC = class interval (1 mph) 146 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 2. Edwards AFB data Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec •See Year 67 68 67 68 67 68 67 68 67 68 67 68 67 68 67 68 68 68 66 67 66 67 Table 1 1021 1070 728 1308 2679 1971 2831 2754 2580 3665 2660 3467 1547 2568 958 2211 1532 1225 894 605 1624 1232 (5) note. Power terms Average Year p Year 67, 68 1045 57-70 67, 68 1018 67, 68 2325 67, 68 2792 67, 68 3124 67, 68 3064 67, 68 2058 67,68 1584 66, 67 750 66, 67 1428 (6) Pooled 1101 1477 2453 2814 3377 3179 2061 1724 1464 1211 1088 960 (7) JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 147 Table 3. Goldstone long-term projected parameters Pf = power term Edwards © Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec ® 66-68 1045 1018 2325 2792 3124 3064 2058 1584 1538« 1225« 750 1428 57-70 1101 1477 2453 2814 3377 3179 2061 1724 1464 1211 1088 960 Goldstone © 66-68 2856 2111 4258 4801 3782 3158 1928 1875 1681 1088 1803 3365 © Projected 2895 2432 4348 4817 3959 3239 1930 1973 1633 1078 2404 3037 Speed factor © c 1.0575 1.2581 1.0776 1.0220 1.0303 0.9911 0.9650 1.00045 0.9711 0.9448 1.1364 0.9251 Long-term parameters a 0.08442 0.07997 0.04506 0.02500 0.03333 0.02363 0.00379 0.04339 0.01267 0.15278 0.09010 0.08072 ® b 0.00068 0.00158 0.00146 0.00223 0.00245 0.00377 0.00743 0.00470 0.00373 0.00061 0.00104 0.00072 Reference Table 2 (6) Table 2 (7) Table 1 (4) ® + 0.7 From computer search 1/cX (2) , Table 1 (1/c) 2 X (3) , Table 1 148 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 GOLDSTONE DATA 1966-68 COMPUTE POWER, G.. j = 1,2 (ye 3 samples per DT Offset 30,000 156 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 2 (contd) Data type 8 9 10 11 "12 Parameter Data type Time, seconds past 0" GMT System noise temperature, S-Band System noise temperature, X-Band Azimuth angle, deg Elevation angle, deg Ambient load, S-band Ambient load, X-band Total bits for data type = 8 Data type Time, seconds past O'1 GMT Microwave polarization angle, deg Microwave mode Total bits for data type = 9 Data type Time, seconds past Oh GMT Microwave polarization angle 1 Microwave polarization angle 2 Microwave polarization angle 3 Microwave mode 1 Microwave mode 2 Microwave mode 3 Total bits for data type = 10 Data type Time, seconds past O1' GMT Microwave polarization angle," deg Diurnal Faraday rotation angle,1 deg Faraday rotation angle 0, deg" Faraday rotation angle + 180," deg Microwave mode3 Signal strength ( ionosphere receiver ) Total bits per block 1-s samples per high-speed data block. Bits /parameter 6 24 12 12 12 12 12 12 102 bits 6 24 18 6 54 bits 6 24 18 18 18 6 6 6 102 bits 6 24 18 18 18 18 6 12 978 bits Least significant bit — S X 10-2 K X 10-1 K X lO-i deg X 10-1 deg X 10-1 °C X 10-1 «C X 10-1 - S X lO-2 deg X 10-2 - s X 10-2 deg X 10-2 deg X 10-2 deg X 10-= _ — _ s X 10-2 deg X 10-= deg X 10-1 deg X 10-1 deg X 10-1 _ V X 10-- Range - 0 - 8,640,000 100-3000 100 - 3000 0-3600 0-900 0-1000 0-1000 - 0 - 8,640,000 0 - 36,000 _ - 0 - 8,640,000 0 - 36,000 0 - 36,000 0 - 36,000 _ ~ _ 0 - 8,640,000 0 - 36,000 0-60,000 0-1800 1800-3600 _ 0-500 Comments ! 1 = linear auto 2 = linear manual 3 = RCP 4 = LCP 1 sample per 20 sec ! 1 = linear auto 2 = linear manual 3 = RCP 4 = LCP Once per block Once per block Offset 30,000 ! 1 = linear auto 2 = linear manual 3 = RCP 4 = LCP Once per block JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 ORIGINAL PAGE IS OF POOR QUALITY 157 r TOWER-MOUNTED EQUIPMENT —1 i- CONTROL ROOM EQUIPMENT—, TEMPERATURE SENSOR nri_ RAIN GAGE r\ SOLAR SENSOR DEWPOINT SAMPLE CELL STATIC PRESSURE HEAD J ^ * • IONOSPHERIC RECEIVER ANTENNA BAROMETER HYGROMETER IONOSPHERIC RECEIVER A-D CONVERTER MAGNETIC TAPE RECORDER TRANSLATOR CALCULATOR TABLE TOP AND DRAWER EXPANDER POWER CONTROL 5- AND X-BAND NOISE TEMPERATURE ANTENNA POINTING ANGLES DAY AND TIME POLARIZATION ANGLE AND _MODE STATUS STANDARD OUTPUT INTERFACE Fig. 1. Meteorological monitoring assembly block diagram 158 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 DIGITAL BAROMETER HYGROMETER POLARIZATION TRACKING RECEIVER A-D CONVERTER AND SCANNER INCREMENTAL TAPE RECORDER TRANSLATOR ASSEMBLY PROGRAMMABLE CALCULATOR POWER CONTROL ASSEMBLY Fig. 2. Meteorological monitoring assembly control rack JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 159 The Minimanual: A New Concept in Operation and Maintenance Handbooks J. Nathenson DSN Engineering Section Reduced fiscal budgets for DSN engineering documentation have necessitated a search for new and more cost-effective methods of producing the technical data required for equipment procurements and for operation and maintenance support of equipment already on-line at the Deep Space Stations. In the major documentation area of technical manuals, a new plan has been devised for achieving substantial monetary savings without sacrificing the integrity of the manuals or their utility as the central source of operation and maintenance information. Called '' the minimanual,'' the new type of handbook has thus far shown an effective response to the exigencies of today's economics. This article describes the minimanual concept, its content and format characteristics, and the results of its first few months of implementation. I. Introduction Traditionally, full-scale operation and maintenance (O&M) manuals have been a compilation of the most pertinent existing technical data on the subject equipment. The categories of information generally included a physical description, a short functional description, installation instructions, pre-operational testing, a func- tional description of controls and indicators, standard and emergency operating procedures, a detailed theory of operation, a circuit analysis, preventive maintenance procedures, troubleshooting procedures, repair and re- placement, qualification testing, a replaceable parts list, and a selection of the most important engineering drawings (i.e., electrical schematics, wiring diagrams, cable diagrams, signal flow diagrams, and logic diagrams). Because they contained the aforementioned wealth of data, the standard O&M manuals were justifiably used as the prime authoritative source of information for opera- tion and maintenance of the equipment. But they have become costly to produce in a time of diminishing funds and blistering deadlines. Clearly, a new concept of technical manual production was needed, one that would provide the same essential information with a lesser time and cost expenditure. 160 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 In examining the problem, it was seen that the three largest cost factors were the writing time, the illustrating time, and the typing time, both for number of hours and cost per hour. Other accrued costs, such as editing time, materials, and printing and binding, were all on the lower end of the scale in dollar value. It appeared that an attack had to be made on the three largest cost factors if the overall price of manuals was to be brought down to a realistic level for the times. By far, the largest expense in manual production was the writing time. It is the responsibility of the writer to gather the existing data from a multitude of sources and to rewrite, reprocess, and properly organize the material into a cohesive whole that conforms to the pre-established outline for the manual. He must also generate new data which may be required for use in the manual alone; such data are obtained from interviews with the cognizant engineers and technicians and from laboring over a great number of schematic and wiring diagrams. This is the time-consuming, hard-core technical writing that has always presented a challenge to cost-conscious manage- ment. In examining the problem further, a few enlightening questions arose. Was it absolutely necessary to have the redundancy of information that the standard manual created? If a large portion of the manual is extracted from existing data in the documentation system, was it practical from an economic standpoint to reprocess the data just for the sake of having a single, all-encompassing manual? Under the current financial pinch, was it still worthwhile to continue the compilation process that gave us large, bulky manuals that were highly authoritative and defini- tive in coverage but were a drain on precious funds that could be used for many other practical purposes? The answers had to be in the negative. Yet, effective O&M manuals were needed. It became a certainty, however, that they would have to be restructured to meet the needs, or limitations, of current conditions. II. Birth of the Minimanual The major element in the solution reached was the reversal of the compilation process. Instead of bringing the operator or maintenance technician to the one, all- encompassing manual for the data he is seeking, we send him back to the original source of the information. This is done by providing the proper source reference in the Table of Maintenance Support Documentation in the manual, unless, of course, the data have been newly generated for the manual itself and are contained within the covers. Thus, the new type of manual becomes a central document, the hub point of a wheel of information whose spokes lead to existing test procedures, engineering drawings, data lists, design specifications, parts lists, commercial handbooks, and other documentation. It becomes, in many instances, the guiding light to essential data rather than the home for it. Christened the "minimanual" for its abbreviated size and coverage, the newly implemented handbook has taken its place alongside the minicomputer and other "minis" as a compact, highly functional element operating in the DSN. It is not, however, solely an index document. The minimanual maintains its integrity as a bona fide O&M handbook by providing all the essential data that are required for a basic understanding of how the equipment works and what it takes to maintain it. The high cost of writer time is cut to a minimum. No longer does the technical writer have to spend countless hours assembling diverse categories of information and rewriting the data into technical manual format. He is required only to identify the data by their existing document numbers and titles and to furnish the references in the Table of Maintenance Support Documentation. His creative efforts are thus confined to the basic task of writing original operation and maintenance procedures and a lucid theory of operation at the technician level. In instances where the engineer himself furnishes adequately written inputs, the writer's task is even further reduced to an editorial function, bringing the cost of the manual down to a very low figure. Permissible shortcuts in writing style and format have also helped to reduce the overall costs. Boilerplate terms and paragraphs, once thought essential for reader comprehension, are not considered valid for minimanual text; the language is required only to be clear and concise, unburdened by stock phrasings and embellishments. Format shortcuts take the form of non-rigid page make- up, the elimination of typeset section headings, the freedom to reproduce existing artwork in its original form, and the use of illustrations sparingly. III. A Harvest of Advantages The question of whether the maintenance technician would be getting short shrift by having to use a minimanual was considered from the beginning. The surprising answer was that not only was he not getting short shrift but he was being aided in his tasks by being forced to go to other sources for much of the peripheral data he needed. Contradictory as this may seem, it must be remembered that the manual is usually the last JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 161 document to be updated for technical accuracy. Indeed, as funds dwindle and sometimes vanish, the manual is not updated at all. It is far, far better for the maintenance technician needing an accurate schematic to go to his blueprint or microfiche file where he is more likely to find the latest revision of the drawing. The same philosophy would apply to parts lists, test procedures, wire lists, cabling diagrams, and the like. The minimanual provides the accurate reference to these documents by number and title; the technician must provide the legwork to obtain the actual data. But it is all worthwhile. No longer will the technician have doubts about the latest effectivity of the schematic in his hand. He will have the most recent revision obtainable, for the drawing system is usually the very first to be kept up-to-date. In producing minimanuals, drastic reductions can be effected both in costs and time schedules. Late beginnings can be offset by fewer pages to be generated. The writer, knowing exactly what information is to be included in the manual and what information is to be supplied by reference only, will have a smoother, more straightfor- ward path to follow and will have a better chance of completing his assignment on schedule. Successful com- pletion on schedule, or ahead of schedule, will mean the availability of documentation where and when it is needed. The reduced costs may possibly create additional funds for other critical documentation or for resolution of equipment problems that were unforeseen. The publications production work on minimanuals calls for no specialized equipment or for any personnel other than the normal repro typist and production editor. As a non-computerized effort, the production work can be quickly and efficiently done in the universally employed methods and procedures for creating camera-ready reproducibles. This is particularly advantageous, since many DSN manuals are prepared by outside vendors, small and large, who do not have computerized equipment for publications graphics. The minimanuals produced in- house by the DSN would likewise require no expensively leased or purchased data processing devices, cathode-ray tubes, magnetic tapes, and the like. A by-product of this standard, long-established production method would be sets of reproducibles for O&M manuals which are all uniform in regard to type face, cameo size, and camera reduction ratio. The manual revision process is thereby simplified, since no matching of diverse type faces and sizes would be necessary. Also, fewer revisions would have to be initiated for the minimanual; most likely, it would be the reference document that would require changing, and not the minimanual itself. Instead of revising two documents, we revise only one—with accompanying cost savings. The minimanual is published in standard 8-1/2 X 11- inch (22 X 28-cm) size and is bound either in thin, flexible cardboard covers or in hard, three-ring binders, depending on engineering preference for the individual manual. In use, it is highly portable and may be taken to any location where it is needed. When it is not being used, it takes up only a minimal amount of desk or bookshelf space. IV. Minimanual Content The restructuring of O&M handbooks into the miniman- ual concept has eliminated four of the standard sections that were previously used: General Description, Installa- tion, Parts List, and Drawings. The three remaining sections, however, do contain the most essential informa- tion for effective operation and maintenance of the equipment. Together with fairly standard front matter and any required appendices, the three sections suffice to provide the on-line technician with the basic facts he needs to do his job. A. Front Matter A combined Title Page and List of Effective Pages is the initial page in the manual. This is followed on the reverse side by a Foreword page that gives a brief description of the equipment's purpose, its physical make- up, and its location in the hierarchy of assemblies, units, groups, and subsystems. The third page contains the beginning of the Table of Contents, List of Illustrations, and List of Tables, which are run in consecutively until completion. A Safety Summary page follows, if one is required. B. Section I—Operation Section I contains a functional description of all controls and indicators on the equipment, which is accompanied by at least one illustration that visually displays the items discussed. This is followed by the usual equipment turn-on procedures and any pre-operational procedures that may be required. The operating procedures themselves give full sequential instructions on how the equipment is operated under normal circumstances. Emergency operat- ing procedures, if any, and equipment turn-off procedures conclude the section. C. Section II—Theory of Operation Section II contains both a general and detailed theory of operation of the overall equipment and its subassemblies. Depending on the electronic, hydraulic, or mechanical 162 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 complexity of the equipment, a circuit analysis is provided to explain or clarify the internal operation of unusual circuits or component parts. D. Section III—Maintenance Section III contains both preventive and corrective maintenance. The preventive maintenance paragraphs provide instructions for inspection, cleaning, and lubricat- ing, as necessary. Corrective maintenance contains a listing of test equipment and special tools, and instructions for calibrating, testing, troubleshooting, and repairing and replacing malfunctioning components. Included in the section is a Table of Maintenance Support Documentation which contains a listing, by name and number, of the most pertinent drawings, specifications, procedures, commercial manuals, and other documents that may be needed for equipment maintenance purposes. E. Appendices Appendices are an optional item in the minimanual concept. Data not properly falling into the three existing sections of Operation, Theory of Operation, and Mainte- nance, but which are considered necessary for inclusion in the handbook, may be placed at the rear of the manual as an appendix. Such items as computer printouts, a glossary of special terms, complicated installation instructions, or special equipment modifications are proper subjects for minimanual appendices. V. Implementation Of the five minimanuals completed to date, the smallest has 16 pages and the largest 130 pages. Writing, typing, and printing costs have been about 40% below the cost of standard manuals. No complications were experienced in the writing and production. The manuals have been released to operations personnel and are being used at the Deep Space Stations. Their utility and effectiveness is under study. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 163 Automatic Control Techniques Used on 64- Meter-Diameter Antenna Power Systems J. Dorman DSN Engineering Section New power plant equipment installed at DSS 61/63 (Robledo, Spain) and at DSS 42/43 (Tidbinbilla, Australia) was designed to supplement the existing equipment for the additional electrical load of 64-m-diameter antennas recently constructed at these sites. The existing power plant equipment (Section A) at each site consisted of manually controlled generators operating at 480 volts. The new equipment (Section B) uses completely automatic generator control operating at 2400 volts. This report describes the automatic controls and also the techniques used for independent or combined operation of both sections. Features provided for possible future operation with commercially produced power, and future automation of Section A equipment are described. I. Introduction The installation of 64-m-diameter antennas at DSS 61 / 63 (Robledo, Spain) and at DSS 42/43 (Tidbinbilla, Australia) demanded increased power-generating facilities. The existing power plant (Section A) operating at 480 volts at each station was supplemented by new generating equipment (Section B) operating at 2400 volts. This progress report describes automatic control features of the Section B equipment, which allow combined or separate operation of the two sections. Controls for future parallel operation of the generators with commercially produced power and future automation of Section A during integration of the two power- generating sections are also described. A brief description of the manual controls performed by an operator in a non-automatic power plant indicates the functions requiring automation and prefaces the descrip- tion of the automatic control. II. Manually Controlled Power Plant Operation At a typical power plant the operator is responsible for the following control operations: (1) Establishes the power load requirements of the system and determines the required number of engine-generators to provide sufficient generating capacity. 164 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 (2) Starts and adjusts the speed of each engine prior to connecting the driven generator to the electrical power system. (3) Sets the engine-generator speed so that a small difference in frequency exists between the incoming generator and that of the power bus before paralleling. This difference in frequency is indicated on a synchroscope by the speed of its pointer rotation. (4) Adjusts the incoming generator voltage to coincide with the power bus voltage before paralleling. (5) Closes the incoming generator circuit breaker to connect the incoming generator to the power system at the precise moment that the generator and power bus are in phase. This is indicated by the synchro- scope pointer at the 12:00 o'clock position. This requirement for correct phase relationship is mechanically analogous to meshing two rotating spur gears at the moment when the teeth are in the correct position. To achieve this condition it is necessary to have a slight frequency (i.e., speed) difference between the power bus and the incoming generator voltage so that the phase angle will cycle and pass the "in phase" condition. If an attempt is made to connect the incoming generator out of phase with the power bus, severe overcurrents and voltage dips will occur and the equipment could sustain heavy damage. In the mechanical analogy, the spur gear teeth would be stripped or damaged. To back up the operator in this operation a permissive synchronization check relay monitors the phase angle of the running and incoming voltages and prevents circuit breaker closing despite control switch operation unless the phase angle difference is close to zero. (6) Having synchronized and then paralleled the new generator to the power system, adjusts the diesel engine fuel manually by a governor control switch. The increase in fuel would tend to increase the diesel-generator speed but this is constrained to correspond with the power bus frequency and, instead, the generator increases its share of the kilowatts (real power load) demanded by the power system. (7) Adjusts the reactive load on the generator by a voltage adjusting rheostat. This rheostat controls the generator field excitation. When the excitation is increased, the voltage of the generator tends to increase but is constrained to correspond with the power bus voltage and instead the generator reactive load (kilovars) increases. NOTE: The constraints on generator frequency and voltage depend on the capacity of the power system. The greater the power load, and number of generators running in paral- lel, the greater the constraints. (8) Monitors the power generation equipment, making necessary adjustments of governors and excitation as required to share the load kilowatts and kilovars between the connected generators in proportion to their individual power ratings. (9) Unloads generators and disconnects them as load demand decreases; then stops the diesel engine of the disconnected generator. III. Automatically Controlled Devices The automatic control devices used to perform the above operations in Section B of the power plant are discussed below. A. Power System Sequencer The power system sequencer (Fig. 1) is built almost completely of solid-state components. It is designed to start and stop the engine-generators as power load increases or decreases. The sequence of starting and stopping of individual machines is manually set by control knobs at the front which allow any machine out of the four installed to be first, second, third or fourth to start. Once preset for starting sequence, the machines stop in the reverse sequence. Following a period of operation of two or three months, the running time of the first engine- generator in the sequence will be greater than the other machines and the sequence will then be manually changed to balance running times. The sequencer is also equipped with control knobs which allow presetting of load kilowatts at which generators will automatically start. Load kilowatt sensing is an integral function of the sequencer. With one machine generating, the first control knob setting determines the percentage of that machine's power capacity at which a second machine should be started and connected to the power bus to share the load demand. The second control knob setting is set at a percentage of the combined power capacity of the running engine-generators which will start a third machine. The third control knob similarly sets the percentage of the combined power capacity of three JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 165 engine-generators which will start and connect the fourth machine. The sequencer presently installed is equipped to handle the four generators presently existing in Section B but can be retrofitted to accommodate the four additional machines in Section A. B. Automatic Synchronizer The automatic synchronizer (Fig. 2) is predominantly of solid-state construction. It differs from the synchronizer check relays previously described by incorporating active controls for regulating the incoming diesel-engine speed. When a machine is started by the power system sequencer, the synchronizer automatically assumes control of the machine, brings it into synchronism, and then automatically closes the circuit breaker to connect the generator to the power bus. Following this operation the synchronizer disconnects itself and engine-generator control is passed to its electronic governor and voltage regulator as described later. Two independent monitors are used in the synchronizer to establish correct synchronizing conditions prior to circuit breaker closing. Both monitors must be satisfied before the generator connects to the power bus. Each monitor checks voltage differential and phase angle difference between the incoming and running generators, and control knobs mounted on the front of the synchro- nizer permit presetting of acceptable voltage and phase angle tolerances which are suitable for synchronizing. If only one monitor signals that synchronizing conditions are met, the circuit breaker will not close, and an indicator light on the synchronizer will signal a malfunction. Other lights on the synchronizer allow visual monitoring of the incoming machine status to indicate overspeed, underspeed, overvoltage, and undervoltage. A feature of the synchronizer is the ability to set the control for circuit breaker closing time, i.e., the short time required for the closing mechanism to respond to its closing signal and physically close its contacts. The synchronizer anticipates the moment of precise synchro- nism and signals the circuit breaker slightly early so that contact closure is at synchronism. C. Electronic Power Sharing Governor Each engine-generator is equipped with an electronic governor control. The fuel setting of the engine is determined by the position of its actuator shaft which is directly proportional to a dc signal from an electronic control assembly. Figure 3 is a block diagram of the fundamental components. This shows that the fuel delivered to the engine, and therefore the electrical power derived from the associated generator, depends on speed and load sensor signals transmitted to the actuator through an integrating and power amplifier. The function of the ramp generator is to control the acceleration of the machine when starting and bringing it up to rated no-load speed prior to synchronizing the generator. Control of the acceleration precludes the possibility of overspeeding the machine on starting. The normal operation of the power plant, unless interconnected with other power sources, will be isochro- nous mode (i.e., constant frequency) with load sharing between parallel connected generators. The connection shown in Fig. 3 going to paralleling lines on other machines provides the load sharing function. Mode switching is provided automatically within the control circuits developed for the system. A short review of fundamentals of stable parallel operation of generators may be of value. D. Review of Diesel Generators Operating in Parallel A diesel generator operating singly and supplying electric power independent of any other generator would normally operate in an isochronous (constant speed frequency) mode. The governor would automatically adjust the fuel setting as the power load varies to keep the speed constant (Fig. 4a). Unless electronic governors are used with forced load sharing provisions, two or more generators cannot be operated in parallel with all generators in isochronous mode. Each machine would attempt to compensate individually for any speed variation and the machines would "fight" each other. The loads on the individual generators would be indeterminate and would swing from no-load up to the maximum load connected to the power bus. This would cause protective gear to operate and disconnect the generators due to overload. One way of overcoming this instability is to speed droop each of the machines in proportion to the power it is delivering. Any machine tending to take a higher proportion of the load will tend to slow down below the speed of the other generators, but as it is forced to stay in synchronism with the others it will shirk the additional load. On the other hand, any machine tending to deliver less than its proportionate share of the total load will naturally tend to increase its speed. As the speed is contrained to correspond with the power system fre- 166 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 quency, this will result in additional load being delivered by the generator (Fig. 4b). The resulting stability of operation is achieved at the cost of overall power system frequency droop with load. Compensation is usually manually performed by governor control switch. A second mode of operation that gives stability is to operate all machines in droop except one which operates isochronously. The isochronous machine functions to maintain power system frequency constant (Fig. 4c). Considering operation under varying power system loads, all machines in the droop mode tend to increase speed as load decreases. The isochronously operating machine shirks its proportion of the load when this occurs, and its share is imposed on the drooped machines to hold them down to system frequency. Conversely, load increase tends to slow down the machines in droop, while the isochronous machine regulates its fuel for the desired speed. The isochronous machine delivers increased load, while the drooped machines shirk any additional load. The price paid for this solution is that the isochronously operating machine can not be run normally at the same load as the drooped machines. It must have reserve power capacity to supply increased load beyond the preset loads of the machines in droop. Another problem can occur if the total load of the system drops below that normally carried by the drooped machines. This causes the isochronous machine to motor on the drooped machines at a speed above that required for 60-hertz operation. The most satisfactory solution of the problem can be achieved only by electrically operated governors which are employed in the power systems. Each governor can be set for isochronous operation with its load sensor control interconnected by bus wires to the load sensor circuits of the other machine governors. Any unbalance in generator kilowatt loading causes an error signal on the bus wires which automatically force-shares all generator kilowatts. E. Voltage Regulation With Cross-Current Reactive Load Control The voltage regulators installed are of the solid-state type. Their function is to maintain a preset generator and power system voltage value when generators are operat- ing singly or in parallel with others. With one generator connected to the power system, the voltage regulator action is to control the excitation of the generator and maintain the preset generator voltage under varying load conditions. The function of the voltage regulator is to compensate for inherent generator voltage droop as load increases, by increasing field excitation. This compensation is achieved by comparing the generator output voltage with a reference voltage, and the error difference is amplified and fed to the exciter. With machines operating in parallel, if the individual voltage regulators attempted to maintain precisely constant individual generator voltage, this would produce unstable reactive load sharing. The problem is very similar in nature to that already described for real power (kilowatt) sharing of isochronous engine-generators. If reactive power is considered instead of real power and the voltage regulator action substituted for the governor action, the similarities in the problem can be noted (Fig. 5). To prevent "fighting" of the voltage regulators and the resulting reactive power load swings between generators, it is common practice to introduce voltage droop into each generator voltage regulator action. This drooping action is required to give stable reactive load sharing and is therefore introduced into the voltage regulator action as a direct function of the reactive component of the generator total load current. Figure 6 shows paralleled generators operating with simple voltage regulator droop compensation. The minimum droop to achieve stable reactive power loading is set by the adjusting rheostats to minimize the power system voltage degradation. Manual voltage adjusting control is used to compensate for the droop and bring the power system voltage within acceptable limits. A better method of maintaining stable reactive load sharing between machines is shown in Fig. 7 and has been used in these power systems. This is achieved by interconnecting the current transformers and voltage regulators of the paralleled generators. The popular term given to this interconnection is "cross-current compensa- tion," and the current transformers are said to be "polygon-connected." The method of connection forces reactive power load sharing between generators without accompanying voltage droop. Referring to Fig. 7 it will be noted that current transformers are connected to their associated voltage regulators in a manner similar to that used for droop control but interconnections (a), (b), and (c) cause a completely different reaction. The individual current transformers generate current i^ When each current value JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 167 is the same, this current passes through interconnections (a), (b), and (c), and the current transformers behave as though their secondary windings are short-circuited. The voltage regulator elements El, E2, and E3 carry virtually zero current, provided the interconnections (a), (b), and (c) have low impedance. For the case indicated, however, generator 1 is delivering more than its share of reactive power, leading to a difference current (Ai) which is superimposed on the balanced value t^ Element El receives most of At and the reactive component of this current is active in causing the voltage regulator to reduce generation excitation. The remainder of Ai passes through the interconnection (a) to the second voltage regulator, through element E2 in the direction causing increased excitation of generator 2. This current then passes through interconnection (b) and through the voltage regulator element E3, which increases excitation of generator 3 and then completes its circuit through interconnection (c) back to the current trans- former. In this case with three machines in parallel, 2/3 of Ai will act through element El to reduce generator 1 excitation, and 1/3 of Ai will act through elements E2 and E3 to increase the excitation of generators 2 and 3. Although it may appear that some of Ai passing through elements E2 and E3 would be shunted by CT2 and CT3, these current transformers represent such high impedances to Ai that their shunting effect is negligible. The foregoing techniques provide all the normal control functions associated with an automatically operated plant. Further consideration had to be given to the controls to allow parallel operation of the automatic plant with an independent commercial power source if this is consid- ered economically feasible in the future. Also, the design allows parallel operation with the manually operated Section A of the power plant. F. Parallel Operation of Power Plant With Commercial Power Source If commercial power is connected to the system, the commercial source will be isochronous. The automated power plant controls will automatically revert to speed droop operation and will carry a preset power load. As described in Subsection D, this provides good, stable operation. The commercial source will provide all variations in power required in excess of that generated by the plant. To allow manual synchronizing of the two power systems and also to preset the kilowatts provided by the generators, the power plant is equipped with a power transfer control device (Fig. 8). This device is actually a simple dc power supply with manually variable output voltages compatible with the paralleling bus wire voltage levels of the electric governors. The output voltage of the power transfer control is manually set to correspond with the value across the governor bus wires by use of a built-in balancing indicator and then manually switched to the bus wires. Following this, movement of a control knob on the device varies the signal voltage on the bus wires which control all governor fuel settings on the connected engine- generator sets. By this control the power plant-generated frequency can be varied to allow manual synchronization and interconnection with the commercial power source. After interconnection, adjustment of the power transfer control knob allows presetting the kilowatts to be contributed by the power plant. Reactive power division between the power plant and the commercial power source is treated differently from the kilowatt power division. It is desirable to keep reactive power load from the commercial system to a low value and use the power plant to supply all reactive power. The generators are fully rated to supply all the reactive load at no fuel cost, while commercial power companies charge for reactive power. The power plant equipment is therefore equipped to monitor the reactive power loading of the commercial power source (Figs. 9 and 10). The monitoring meter is equipped with manually settable contacts which close whenever reactive power flows in the commercial power source interconnection. The contacts drive a motor-operated variable transformer which injects a voltage into the cross-current compensa- tion circuit of the generator voltage regulators as shown in Fig. 9. When the variable transformer is in the null position, corresponding with its center point, the voltage induced in the cross-current circuit is in phase with phase 2 voltage, and this has no effect on the voltage regulators. When the variable transformer is in other positions, the vector phase angle of the induced voltage changes, and the quadrature component of this voltage acts on the voltage regulators to raise or lower the generator excitations. The resulting effect is to maintain commercial power source reactive 168 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 power loading within the manual settings of the monitor- portion of the load kilowatts and kilovars while the ing meter. manually operated section will supply a variable portion of the load as power demand varies. Complete integration of Sections A and B of the power G. Parallel Operation of Power Plant Sect.ons A and pUnt {^^ j^ will provide a totally auto£ated system, incorporating all the automatic features to both The present configuration demands that the manually sections of the generator plant. The operation of the operated Section A be considered as an isochronous power integrated system will be isochronous with zero frequency source. This means that the automatic Section B must be or voltage droop, load sharing of kilowatt and reactive operated in the droop mode (governors and voltage load between generators in proportion to their ratings, and regulators). The automatic Section B will deliver a preset automatic starting and stopping control of all generators. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 169 i,.."«.«hw "' . - . - , . • • * ft iI I I L I I I Fig. 1. Power system sequencer c» Auto-Synchronizing Relay Fig. 2. Automatic synchronizer 170 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 CURRENT TRANSFORMERS +24 V DC INPUT SECTION CONTROL SECTION Fig. 3. Block diagram of electronic governor system JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 171 (a) SINGLE GENERATOR OPERATION - ISOCHRONOUS MODE HORSE POWER—" AND KILOWATT LOAD (a) SINGLE GENERATOR OPERATION - CONSTANT VOLTAGE MODE (b) MULTIPLE GENERATOR OPERATION - DROOP MODE tli So 5; Sf ^^^ 11 1 1 I ^__^^ ^^^ kW I kW 2 GEN 1 GEN 2 TOTAL kW LOAD = kW I kW3 GEN 3 kW 2 + kW 3 kW 1 = kW 2 = kW 3 (c) MULTIPLE GENERATOR OPERATION - ONE GENERATOR ISOCHRONOUS So LLJ LLJ a- a- I kW3 GEN 3 (DROOP) kW 1 kW 2 GENT GEN 2 (DROOP) (ISOCHRONOUS) TOTAL kW LOAD = kW 1 + kW 2 + kW 3 kW 2 = kW 3 = CONSTANT: kW 1 VARIABLE Fig. 4. Diesel-generator operating modes REACTIVE LOAD, kVAr (b) MULTIPLE GENERATOR OPERATION - VOLTAGE DROOP MODE O I VOLTAGE I DROOP TOTAL kVAr LOAD = kVAr } + kVAr 2 + kVAr 3 kVAr } = kVAr 2 = kVAr 3 Fig. 5. Kilovar loading of generators 172 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 r kW "1 CIRCUIT BREAKER CURRENT TRANSFORMER ,-r-U VOLTAGE REGULATOR -r . "i 1 POWER SYSTEM LOAD GEN 1 GEN 2 GEN 3 NOTE: REACTIVE COMPONENT OF ib IN DIRECTION SHOWN REDUCES GENERATOR EXCITATION THROUGH VOLTAGE REGULATOR ELEMENTS El, E2, AND E3 Fig. 6. Generator voltage regulators in droop mode JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 173 CIRCUIT BREAKER CURRENT TRANSFORMER !b + A! tj 5 V0 1 ' •^ : ib + 1/3 Ai -» ' 1 i.| >— VOLTAGE REG i < /-(a) CT2— ' 1 ' ,^| 1 J i ib + 1/3 Ai -» Lii 1 r> 4 C13—J 1 ' 1/3!) : L ~ rii iii ib + 1/3 Ai — ^ 1 L| 1 kW -vw POWER I SYSTEM LOAD | •^YYV\ kVAr NOTE: REAaiVE COMPONENTS OF Aio GEN 1 0 0 REDUCE EXCITATION OF GEN 1AND INCREASE EXCITATION OFGEN 2 AND GEN 3 GEN 2 GEN 3 Fig. 7. Generator voltage regulators with cross-current compensation Fig. 8. Power transfer control 174 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 kW J t <: GE , ) N r^ \ JJ 1 1 ' L _, ^-VOLTAGE REG 1 1 POWER 1 | (I GE NOTE: 3 1 1 | | | ~ j t AUXILIARY | | ^—VARIABLE ^^^ | | \ TRANSFORMER \ —ML rf, iV-T^ If _rf,->ir ,-L *3j k %n-J •^ I DRIVE A IMOTOR^ / T T \ / RAISE LOWER \ KILOVAR MONITOR LIMIT LIMIT \ $"-OVM METER CONTACT CONTACT J— TRANS- — \ / DUCER CONTACTS SHOWN -U \ t / ' CLOSED WHEN \ / COMMERCIAL POWER \. <-> ./ USED ^ — LOAD 1 4 COMMERCIAL | POWER Fig. 9. Simplified circuit of modified cross-current compensation of generator voltage regulators when commercial power connected JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 175 COMMERCIAL POWER V2 APPLIED / VOLTAGE / WHEN / NOT IN / NULL POSITION — . / i /—APPLIED VOLTAGE / AT NULL POSITION / i/\r CXT r^s* VI v ' v3 quad 7 11 / | VARIABLE JUUUU«~«w«s 1 1 1 PPLIED I--. OLTAGE 1 j^ uu /^uuJ TRANSFORMER NULL POSITION W \ ^^— SLIDER POSITION DEPENDING ON COMMERCIAL SOURCE KILOVARS Fig. 10. Voltage vectors applied to voltage regulator cross-current compensation circuits 176 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Upgrade of Heating System for Energy Conservation at DSS 62, Cebreros, Spain J. M. Urech Station Director, Cebreros, Spain This report presents a description of the modification performed as part of the energy conservation program at the Cebreros, Spain, Deep Space Station (DSS 62) and the results obtained. The article was excerpted from the final engineering report on this project by E. H. Thorn. I. Summary This report presents a description of the modification performed as part of the energy conservation program at the Cebreros, Spain, Deep Space Station (DSS 62) and the results obtained. The modification is based on the elimi- nation of the air-conditioning boiler and the heating of the operations building by the waste heat from the power generator engines. Consequently, by transporting dissi- pated heat from the powerplant to the operations build- ing, this modification will represent an energy savings of 70,000 liters per year in boiler fuel and a cost savings (at current prices) of $12,000 per year. II. System Comparison The following is a comparison of the major heat pro- ducing components comprising the former and the new heating systems. A. Boiler (Former System) The boiler is located in the operations building and was previously used to provide hot water for heating and ordinary purposes. It is an automatic unit capable of maintaining a constant temperature of 65-85 °C and a flow of 220 liters per minute up to a maximum 140,000 kcal/hour. The annual fuel consumption of this unit is 70,000 liters under normal weather conditions. B. Generators (New System) The station powerplant contains four diesel generators capable of producing a total of 1,850 kW, divided as follows: Three 500-kW units One 350-kW unit Normal station operations require about 400 kW with a normal generator configuration of two generators on the JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 177 line. Generator engine cooling is accomplished by radia- tors with electric fans. In this arrangement, the cooling water reaches a temperature of 85 °C — heat which is wasted into the atmosphere. The heat dissipated in the radiator is proportional to the load. Figure 1 shows the upper and lower load limits over a 24-hour period, as well as the heat dissipated at each limit. As indicated, the heat wasted at the lower limit (190,000 kcal/hour) is higher than the maximum output of the referenced boiler, thus providing a clear advantage over the former system. III. Implementation A. Technical Background The possibility of bringing the water from the engines directly to the operations building was rejected primarily for the following reasons: (1) Danger of failures which would affect the engines. (2) Incompatibility between circuit flows. (3) Pressure drops or increases which would jeopardize engine operation. (4) Static pressure increases, caused by variations in building heights, which would affect the engine circuit. These and other reasons recommended the use of a heat exchanger in order to maintain the independence of both circuits while transferring heat from one to the other. Heat exchanger capacity permits a maximum heat trans- fer of 225,000 kcal/hour from the primary to the sec- ondary circuit when the temperatures of both circuits are: Primary Secondary inlet 85 °C outlet 65 °C inlet 60 "C outlet 75 °C B. Configuration and Materials Since the amount of heat to be dissipated in the primary circuit is always greater than the requirements of the second circuit, some of this heat must continue to be dissipated in the radiator. To facilitate this function, a three-way motorized valve has been added. This valve divides the water flow to permit direct flow to the engine and indirect flow via the radiator. In this way, the water entering the engine can be maintained at 60°C. The temperature of the return water is kept at 60 °C to ensure that the thermostatic bypass of the engine permits sufficient flow in the outside circuit and thereby main- tains adequate heat exchanger performance. Each engine has been provided with a proportional thermostat con- nected via a selector switch to the heating engine. This controls the motorized valve which maintains the inlet temperature at the pre-established 60 °C. The valve drive motor contains a spring that returns the valve to the radiator position. This setting allows the entire flow to circulate through the radiator. The purpose of the device is to eliminate the possibility of an engine shutdown due to overheating indirectly caused by an electrical failure in the valve control. C. Costs It should be noted that the implementation has been performed employing on-hand or surplus materials when- ever possible. Furthermore, no additional costs for project preparation or implementation are applicable since these tasks were undertaken entirely by station personnel. In summation, this item includes only the costs of purchased materials as follows: Heat exchanger $ 4,330 Pumps 1,025 Three-way valve 687 Insulation 2,760 Piping, manual valves, supports, screws, etc. 5,629 Total $14,431 IV. Conclusions System operation has been completely satisfactory with an available water flow of 250 liters/minute and a tem- perature on arrival at the operations building of 71 °C. Moreover, a potential increase of 60,000 kcal/hour has been obtained over the previous system. Despite the fact that no extremely cold days have been experienced since its implementation (minimum tempera- ture 10 °C), the new system promises to yield excellent performance due to its large heat reserve. 178 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 400 - o o S 100 - 200 300 400 ENGINE LOAD, kW 500 600 Fig. 1. Engine heat dissipation vs generator load JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 179 N76 14309 Pseudo-DRVID: A New Technique for Near-Real-Time Validation of Ranging System Data A. L. Berman Network Operations Office Near-real-time validation of doppler and angular radio metric data has been quite successful and an established fact for the last decade. Near-real-time valida- tion of ranging system data, however, has for the most part been ineffective. Reasons are here presented as to why the doppler and angle validation tech- niques cannot successfully be applied to ranging system data. A new technique is described which can validate sequential range acquisitions in near-real-time to the 10-meter level. I. Introduction Near-real-time validation of doppler frequency data (the primary orbit determination data type) has been generally performed since 1965 and has proved to be enormously successful in identifying problem areas within the Deep Space Network (DSN) tracking system in a convenient and timely fashion. On the other hand, near-real-time validation of ranging system data (the secondary, but very important, orbit determination data type), although an oft-iterated and earnestly sought after goal, has in general proved both elusive and unsatisfac- tory. In particular, near-real-time validation of ranging system data from the current prime ranging system, the Planetary Ranging Assembly (PRA), has (until recently) been superficial and unevenly performed. The reasons why the current near-real-time radio metric data valida- tion techniques, which have proved so successful with doppler data, fail when applied to ranging system data become apparent when the differences in the nature of doppler data acquisition vs ranging system data acqui- sition are considered. The crux of these differences is that the doppler system makes frequent measurements which are independent in and of themselves, while the PRA makes infrequent measurements of a quantity (not identically range!) which will, when combined with very precise orbital foreknowledge, produce a range measure- ment. In the following sections, the difficulties with and the inappropriateness of applying the current near-real- time radio metric data validation techniques to ranging system data will be explored. Finally, a new and far" more satisfactory technique, referred to as "Pseudo- 180 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 DRVID"1 will be presented, in combination with some preliminary, but illustrative results of the new technique. II. Description of Current Near-Real-Time Radio Metric Data Validation Techniques The current near-real-time radio metric data validation techniques, which have so successfully validated ac- quired radio metric data for navigation purposes and have additionally served to rapidly pinpoint malfunc- tions in the tracking system, begin with the simple ex- pedient of comparing each time-dependent radio metric data sample with a corresponding "predicted" value. To facilitate a discussion of the technique, the following notation is defined: If X(t ) = radio metric data type then where i ) = the "residual" of data type X at time tt = acquired ("actual") data type X at time t^ — expected ("predicted") data type X at time t f If one has only a single or perhaps a few residuals during any particular time interval of interest, the amount of information that is yielded by this process is perforce severely limited. Basically, about the most that one can conclude with reasonable assurance is that: Occurrence Conclusion Large residual Invalid data Small residual Valid data, with the residual indicative of the magnitude of the prediction error One of course strives to use accurate predictions in the process as it is the level of confidence in the predictions which determines what is "large" and what is "small" for Differenced range vs integrated doppler. The name was chosen be- cause one can discern a faint similarity between the relationship of "Pseudo-DRVID" to actual (PRA-produced) DRVID and of "Pseudo-Residuals" to actual (orbit-detennination-produced) angle and doppler residuals. the above. On the other hand, if one has a large popu- lation of residuals to work with, as is the usual case with the acquisition of both doppler and angular data, one can infer a great deal in addition to the above. These inferences can be broadly categorized as follows: (1) Signature. By examining a large population of re- siduals, one can detect patterns ("signatures") of various types of systematic tracking system mal- functions. A prime example of this effect would be an error in the station time standard. (2) Noise. By examining the standard deviation ("noise") of a large population of residuals (after a least squares curve fit), one can detect tracking system malfunctions which result in random errors. A prime example of this effect would be a failure of the doppler resolver counter. As has already been stated, the above procedures have worked very well indeed for validating doppler data for navigation purposes as well as monitoring the health of the tracking system. It is now necessary to examine the applicability of the above techniques to Ranging System data (specifically the PRA). III. Applicability of Current Near-Real-Time Radio Metric Data Validation Techniques to PRA Data The PRA has been designed for use in cases where a very accurate estimate of the range at any given time already exists. The relationship between range and the output of the PRA is as follows: R(t) = K[M(t)] + RPRA(t) where R(t) — range at time * K = ambiguity resolution factor (a quantized input, in units of R(t)) M(t) — integer, determined from independent orbital knowledge RPRA(t) = "scaled" output of the PRA (i.e., in the same units as R(t)) The ambiguity resolution factor K is extremely small when compared to the absolute range R, and in practice is selected (from 20 possible values) to be somewhat JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 181 larger than the current navigation estimate of the range uncertainty. It is not chosen indiscriminately larger than the range uncertainty as there is a penalty associated with increasingly large Ks ( lengthened acquisition time ) . BPRAA(tt) In the past, it has always been somewhat blithely as- sumed that a "range" residual could be obtained from the PRA output and range predictions, and most prob- ably it has been this assumption which has confused the issue of ranging system data validation and stymied efforts to approach the problem with differing view- points. The pith of the matter is: One cannot obtain a "range" residual from PRA output as one directly obtains doppler residuals from doppler data; one can only obtain, at best, a "PRA output" residual! It is then necessary to inquire as to the composition and usefulness of a "PRA" residual; more specifically, one would like to determine what relationship the PRA resid- ual bears to a range residual. The determination of this relationship is as follows: Let the actual range at a time t f be and so that a valid PRA acquisition would yield fi) ss RPRAA(t4) (The above assumes that RPRAA is not within a few meters of 0 or K — this event having a very low probability of occurrence for typical acquisitions.) Now assume that the predictions to be used have an error Z(ti) so that Z(f;) One can now calculate a "predicted" PRA output RPRAP(ti) = RP(ti) modulo K = {K[M(*i)] + RPRAA(t{) + modulo K Having now obtained RA, Rp, RPRAA, and RPRAP, one can construct a range residual and a corresponding PRA residual as follows: + RPRAA(*i) + Z(ri)} modulo K Z(ti) - ]K ifRPRA(fi) Z(*i) + /K 1 = integer / = integer The final result is that: AR(fi) = ApK.i^Oif 0 < RPRA(t,) i) if RPRA(t,) + Z K Since K is selected on the basis of being only some- what larger than the estimated uncertainty (~Z(£j)), the inequality (above) will occur quite frequently, and hence there is no way that a PRA residual can be con- fidently equated to a range residual in near-real-time. Rendering the PRA residual even more useless in an absolute sense is the modulo character of the PRA data, which means that no matter how the PRA might mal- function, an "invalid" PRA residual statistically has an (averaged) 50% chance of being a smaller (magnitude) number than the corresponding "valid" PRA residual (assuming prediction accuracies are never significantly below the smallest possible K, or about 300 meters) — this property being in sharp contrast to the doppler and angle situation. To illustrate with a very possible case, consider the following: Let = 18.2 km 182 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 and Then and Z(t i) = 9.1 km = -9.1km / -9.1 km if RPRA(fj) < 9.1 km - | +g>1 j^ if RPRA(t .) > 9 i ^ The above results in the following: (1) 50% chance of &PU.t =£ Aff. (2) 50% chance of any random PRA output yielding a smaller absolute PRA residual than the correct PRA residual. Finally, even if one could somehow obtain range re- siduals in near-real-time from PRA residuals, the powerful tool of examining a population of residuals for signature and noise, as is done with angle and doppler validation, would not be available because only a few PRA range acquisitions are normally made during a typical pass. To recapitulate: past efforts to validate PRA data with the same techniques used so successfully to validate dop- pler and angle data were foreordained to failure because: (1) It was falsely assumed that one could obtain range residuals, when in fact one can only obtain "PRA" residuals. (2) Recause of the very small (relative to absolute range) span of PRA output (0 ^ PRA data < K), invalid (or random for that matter) PRA residuals are (on average) the same size as valid PRA resid- uals, thus to a considerable extent destroying the usefulness of a PRA residual — in marked contrast to the situation with doppler and angle residuals. (3) Since few PRA measurements are usually made in any given pass, little "signature" or "noise" infor- mation would be available, even if range residuals could be reconstructed from PRA residuals in near- real-time. IV. The Pseudo-DRVID Technique It was shown in Section III that the technique of directly forming "actual" minus "predicted" residuals cannot be effectively applied to PRA data; the Pseudo- DRVID technique can be viewed as a slightly rearranged variation of the basic residual scheme, viz: Consider that two or more PRA ranging acquisi- tions are performed within a single pass. Allow the earliest PRA acquisition to be the "predict," which is updated to the time of a latter PRA ranging acquisition (the "actual") with ease and extreme accuracy by means of integrated dop- pler between the two PRA acquisitions. Using this process a "range" residual between the two PRA measurements can be formed which will include only the actual PRA data errors plus DRVID. Normally, the DRVID effect is on the order of meters2, so that one might expect vali- dation between the two acquisitions down to the several-meter level. The pivotal feature of this scheme is that it obviates the necessity for any orbital predictions, which is the very require- ment that hamstrings the current techniques when applied to PRA data. The derivation of the Pseudo-DRVID equations begins with the two way doppler equation 02 = 96 -i2TrsF« + bias where TSFB = track synthesizer frequency (cps) at received time TSFT = track synthesizer frequency (cps) at transmitted time fdr \[ -rr ) = 2-way uplink range rate, m/s "' -TT- \ = 2-way downlink range rate, m/s c— speed of light, m/s bias — doppler bias frequency (cps), normally: Block III receiver, 106 cps Block IV receiver, 5 X 106 cps 2Except near solar conjunctions, when DRVID becomes 10s or 100s of meters. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 183 However, during a ranging pass the TSF is not (usu- ally) changed, so that TSFR = TSFT and so that one has + bias 240 / TSF\ r/dr\ /dr\ "I -"aK— )|M, +U)J+bias or Assuming that the difference in round trip range (RTR) is desired between the times ta and tt (and ignoring DRVID), one merely integrates the above equation as follows: / [D2 - bias] dt Jt. /•'• 240 /.. "22T' defining CNTS(t) = doppler counter reading at time t, cycles with RTR = round trip range, m rup = uplink range, m rdn = downMnk range, m —\ - — ( ' JA. \ **P/ /"*' (D2 - bias)* = [ ' [D2] dt- { " (bias)cft yt. y*. ./«„ /" *' (D2) dt = CNTSfa) - CNTS(ta)Jt. tt (bias) eft = (*i - ft,) (bias) . and /"'6 d = -%f (Tup + Ti"> dt f t t f t " = I d(rup + rdn)= / d(RTR)J (« y «„ = RTH(t») - finally yielding _ CNTSfa) - CNTS(t«) - bias (tt - ft.) 240 /TSF\6 " ~ Thus, simply by using the TSF, the doppler bias, and the doppler (cumulative) counter readings, one can rather easily and extremely accurately translate one range to a subsequent range, and hence be in a position to validate sequential PRA ranging acquisitions. The complete algorithm is detailed below. It is essen- tially the equation above; however, it is presented in the form Pseudo-DRVID = , ft,) - ADOP(tt, ft,) 184 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 where where ( RPRA(tb) - RPRA(ta) J if RPRA(tb) - RPRA(fa)^:0 \ RPRA(tb) - RPRA(O + K (ifRPRA(tb) - RPRA(ta) < 0 and [RTR(tb) - RTR(ta)] modulo K - Rrfl(t.)] modulo K + K Additionally, doppler counter rollovers are accounted for, the explicit functional dependence of K upon the number of ranging components is displayed, and the quantities are scaled to be in meters. Assume two PRA acquisitions at acquisition times of ta and tb and define PRTR(t) = PRA data in RU, for acquisition time (TO) = t N = number of components RLOVRS — number of doppler counter "rollovers" between ta and tb K so that = K(N) =48(TSF) (2-V-no) 48(TSF) [PRTR(tb) - PRTR(ta) + Y] where JO if PRTR(tb) - PRTR(ta) > 0 *+io if pflTR(*s) - PRTR(ta) < 0 and ( 221 / c \ ADOPfot.) = 196(240) (rSFJ [C^TS(^) - CNTS(t«) + RLOVRS(1010) - bias(f6 - «.) W 0 if RrR(ft) - RTR(fa) c(VJSFJ 3 with the final result of Pseudo-DRVID = V. Pseudo-DRVID Results , ta) - ADOP(t6, ta) Tables 1 through 4 present results of applying the Pseudo-DRVID algorithm to selected Mariner 10 rang- ing passes. The tables are arranged to span the type of results possible ( i.e., in terms of percent of valid acquisi- tions and degree of correspondence for the valid acqui- sitions) as follows: Table DSS Date, 1975 Characterization of results 1 2 3 4 43 63 63 43 March 15 March 15 February 12 February 27 Excellent Excellent Fair Poor Table 5 presents some miscellaneous statistics for the data presented in the first four tables (it should be noted that all the Pseudo-DRVID results in Table 1 through 5 have been presented as absolute differences). The net result of the data presented in the tables is to show that the Pseudo-DRVID algorithm can validate good (sequen- tial) PRA acquisitions by showing correspondence be- tween acquisitions down to the 10-meter level. VI. Conclusions Past attempts at ranging system near-real-time data validation have generally been ineffective, primarily because the vast differences in the nature of ranging system data and, in particular, PRA ranging data, as compared to doppler and angular radio metric data, were not completely considered—thus leading to attempts to use techniques for ranging system data validation which are not really applicable. The "Pseudo-DRVID" tech- nique presented here can validate sequential PRA acquisitions down to the 10-meter level and is now opera- tional for near-real-time validation of PRA data. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 185 Acknowledgment The author wishes to acknowledge the contribution of Larry E. Bright, who coded the pseudo-DRVID algorithm for operational use and processed the Mariner 10 data presented herein. Bibliography Herman, A. L., "Validation of Sequential Range Measurements—Or, Do-It- Yourself DRVID," IOM 421G-75-048, Jet Propulsion Laboratory, Pasadena, Calif., March 18, 1975 (an internal document). Martin, W. L., "Information Systems: A Binary-Coded Sequential Acquisition Ranging System," Space Programs Summary 37-57, Volume II, Jet Propulsion Laboratory, Pasadena, California, May 31, 1969. Spradlin, G., and Schlaifer, R., "The Planetary Operational Ranging Subsystem (PRA)," IOM 421G-75-019, Jet Propulsion Laboratory, Pasadena, Calif., Jan. 30, 1975 (an internal document). 186 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 1. Pseudo-DRVID PRA data validation, DSS 43, March 15, 1975 Table 3. Pseudo-DRVID PRA data evaluation, DSS 63, February 12, 1975 p* 21:15:00 23:25:00 00:55:00 02:50:00 06:00:00 20:30:00" 04:30:00 05:15:00 Pseudo-DRVID Meters RU Valid acquisitions 20:30:00 5 17 22:00:00 7 23 00:10:00 2 8 01:40:00 9 32 03:45:00 5 19 Invalid acquisitions 19:45:00 272 953 03:45:00" 33,957 118,851 03:45:00" 287 1,004 'Times in GMT. "The "good" acquisition of the pair. Table 2. (TO)* 09:45:00 10:45:00 11:45:00 13:15:00 14:15:00 12:15:00 13:45:00 Pseudo-DRVID PRA data validation, DSS 63, March 15, 1975 Pseudo-DRVID(TO)' Meters RU Valid acquisitions 09:15:00 16 57 10:15:00 14 51 11:15:00 8 27 12:45:00 6 22 13:15:00 13 46 Invalid acquisitions 11:45:00" 2,349 8,222 13:15:00" 40,406 141,421 'Times in GMT. "The "good" acquisition of the pair. OF POOR C Tables. Pseudo-DRVID PRA >\(VF, IS tUA.L'1 Station Date 1975 Mean, 43 March 15 5.6 63 February 15 11.4 63 February 12 11.3 Combined above 9.3 Pseudo-DRVID(TO)' (T0)a Meters Valid acquisitions 06:55:00 06:20:00 5 07:40:00 06:55:00 5 10:30:00 09:05:00 26 11:15:00 10:30:00 9 Invalid acquisitions 08:30:00 07:40:00" 4,686 09:05:00" 08:30:00 8,765 09:45:00 09:05:00" 74,871 12:45:00 11:15:00" 23,408 'Times in GMT. "The "good" acquisition of the pair. RU 19 19 93 33 16,401 30,676 262,050 81,929 Table 4. Pseudo-DRVID PRA data evaluation, DSS 43, February 27, 1975 Pseudo-DRVID(TO)' (TO)' Meters Valid acquisitions 02:55:00 00:35:00 62 Invalid acquisitions 00:35:00" 18:50:00 24,216 00:35:00" 20:30:00 23,336 00:35:00" 22:20:00 2,475 00:35:00" 23:30:00 60,738 01:45:00 00:35:00** 18,731 05:00:00 02:55:00** 10,347 'Times in GMT. "The "good" acquisition of the pair. evaluation statistics Valid acquisitions m Standard deviation, m 2.6 4.2 10.0 6.2 RU 219 84,756 81,676 8,662 212,584 65,560 36,214 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 187 Automatic Total Recall System Test Program G. L. Mock Network Operations Office The Automatic Total Recall System (ATRS) Operational Program provides a very important data retrieval function from the Deep Space Stations to the Mission Control Center. The operational integrity of this program must be verified after any software changes have been made to it or after any hardware modifications have been made at the Deep Space Stations. The ATRS Test Program provides this capability by simulating the ATRS function of the Mission Control Center. I. Introduction The Deep Space Station (DSS) Telemetry and Com- mand Subsystem (TCD), along with the Ground Communi- cations Facility (GCF), provides a communications link between the spacecraft and the Mission Control Center. The TCD is responsible for transmitting commands to the spacecraft and recovering incoming telemetry data from the spacecraft. The TCD generates a real-time Digital Original Data Record (DODR) of all telemetry and command data transmitted over the communications link between the DSS and the Mission Control Center. If, for any reason, an incomplete data record is received at the Mission Control Center, the DSS can replay the data from the DODR by using the Automatic Total Recall System (ATRS) Operational Program (Ref. 1). II. Purpose The purpose of the ATRS Test Program is to provide an independent on-station means of testing and verifying the ATRS function at the DSS. This task is accomplished by simulating the Mission Control Center ATRS function and performing tests on the response made by the ATRS Operational Program. This effectively eliminates the need for scheduling the Mission Control Center for the development, implementation, and testing of the ATRS function until it is considered operational. III. Program Structure The ATRS Test Program was designed and imple- mented for use on either the Digital Instrumentation 188 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Subsystem (DIS) or Telemetry and Command Processor (TCP) computers located at the DSSs. The program was designed to be mission-independent and implemented in modularly structured assembly language to facilitate future expansions and modifications. The program resides on magnetic tape and is loaded by means of a paper tape bootstrap loader. IV. Functional Description Under operator control, the ATRS Test Program formats and displays ATRS initialization and recall request blocks and transmits them to the ATRS Operational Program over the high-speed data (HSD) or wide-band data (WBD) communications lines. These blocks contain descriptions of, and requests for, blocks of data from the DODR. Additionally, the ATRS Test Program retains the information from these blocks as a means of testing the ATRS Operational Program's responses. When the ATRS Operational Program receives both the initialization and recall request blocks, it searches the DODR and plays back the data over the HSD/WBD communications line to the ATRS Test Program. The ATRS Test Program receives these blocks and compares the data block type, the data block time, and the sequencing of the blocks against the reference informa- tion. Any discrepancies are noted by the outputting of error messages on the operator-selected input/output device. The ATRS Test Program also has the capabilities of selectively displaying any data block received and writing its own ODR of all data blocks received. V. Conclusions The ATRS Test Program is a very useful tool in that it has helped to automate the implementation and testing of the ATRS function at the DSSs. It also has proved to be very useful in the development of the ATRS operational software due to its ability to simulate the ATRS function of the Mission Control Center. Figure 1 shows the configuration and interface of the ATRS Operational Program and the ATRS Test Program at the Deep Space Stations. Reference 1. Hlavaty, F. M., "Automatic Total Recall Program for Replay of DSN 7-Track DODRs," in The Deep Space Network Progress Report 42-25, pp. 137-141, Jet Propulsion Laboratory, Pasadena, Calif., Feb. 15, 1975. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 189 DEEP SPACE STATION ATRS OPERATIONAL PROGRAM ATRS TEST PROGRAM 7-TRACK DODR o 7-TRACK DODR DATA DATA REQUEST KEYBOARD TCP INPUT/PRINT TTY "" " KEYBOARD INPUT, ERROR MESSAGE OUTPUT DIS OR ' • TCP TTY MESSAGES INITIALIZATION RECALL REQUEST STATUS RECALL DATA Fig. 1. Automatic Total Recall System test configuration 190 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 N76 14310 Operations Analysis of Intermediate Data Record Production in the Viking Era D. C. Card Network Operations Office As a final step in the operations analysis of Intermediate Data Record (IDR) production capability, dynamic system simulation models have been constructed and executed within the context of the General Purpose Simulation System (GPSS) applications program on the Univac 1108 system. The dynamic models simulate all activity in the DSN ground systems which contributes to data flow characteristics and ultimate throughput times for the IDRs. Two basic model versions have been constructed, representing alternative configurations at the merge processor: Model A simulates 4 tape-drive units at the merge processor; Model B simulates 8 tape-drive units. It has been confirmed subsequently that the 8 tape-drive configuration will be implemented. Both basic models were "driven," in dynamic simulation runs, by the same "worst case" mission support profile, representing the heaviest possible support requirement during the Viking encounter and planetary experiment period. Quantitative specification for system parameters, flow logic, and support profiles has been derived from internal JPL documents. Much of the essential specification for dynamic models was immediately at hand as a consequence of earlier "static" analysis studies. A 4 tape-drive configuration was found to meet a 24-hour throughput time requirement for IDRs. However, the simulated facilities are heavily loaded by the "worst case" profile; therefore, significant deviations from assumed facility availability or operational capabilities may have a critical effect upon performance to the requirement. With an 8 tape-drive configuration, the Merge Processor easily meets the throughput time requirement. The simulated facilities show no severe utilization JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 191 stress, and the configuration provides sufficient input/output capability that recall operations are not delayed on-queue waiting for Merge Processor facility availability (not the case for the 4 tape-drive configuration). I. Introduction This article reports the principal results of an opera- tions analysis task which has culminated in the develop- ment and application of computer-based dynamic simula- tion models of data flow in the DSN systems essential to the production of Intermediate Data Records (IDRs). The immediate motivation has been to determine whether specific systems configurations possess sufficient capability to produce IDRs within 24 hours of end-of-pass during heavy demand periods on the network, such as that anticipated during Viking encounter and planetary experiment. The effort is the logical extension of a series of operational capabilities studies; it has been carried out in the period from March 1 to June 30, 1975, resulting in the completion of working, programmed simulation models of mission data flow from deep space station (DSS) site to IDR production. The impetus for analyzing the operational capabilities to produce IDRs was provided by a network commitment to provide engineering and science IDRs within 24 hours from the end of the associated station tracking and data acquisition pass. This performance requirement originally arose as a defined requirement of the Viking project. It was subsequently reflected as a general DSN performance requirement in the DSN Operations Control Center Requirements. Because of anticipated heavy support demands upon the Network during the Viking era, there was concern in the Network Operations organization that such a performance requirement might not be met uniformly using the planned facility configurations. In response to these concerns, several "static" time-line studies were per- formed. These studies showed that, under ideal conditions and in a "worst case" network loading period, the planned configuration with 4 tape-drive units at the Merge Processor appeared to be adequate to meet the require- ment. However, the time-line approach was essentially deterministic in structure and could not admit random events, such as equipment failure or operations variability, just from a practical standpoint. As a result, the bounds on feasible system and operations characteristics which would permit the requirement to be met remained uncertain. The logical continuation of the operational performance analysis was to construct relatively detailed dynamic models to simulate operations, using a digital computer. This approach makes accessible results that reflect a broader, more complete representation of the system characteristics which will affect performance, including the pertinent random events. The extended dynamic simulation analysis has been performed using the General Purpose Simulation System (GPSS) program on the 1108 system. This choice was made on the basis of accessibility of the 1108 systems programs and availability of GPSS modeling expertise in the Network Operations organization. The results of this approach to operations analysis for a complex system operation have the further distinction of demonstrating both the effectiveness and utility of this technique as applied to network operations analysis. II. Objective The principal objective of this operations analysis effort has been to develop an effective tool capable of providing the information necessary to determine whether or not designed network control configurations, along with their specified functional design, will meet established require- ments. The general criteria for effectiveness which have been followed in this effort are: (1) The models and analytic methods used should be valid representations of the operating systems and their functional design; further, the representations should be visible such that validity may be assessed. (2) The analytic models should permit the incorporation of realistic system specification and assumptions, insofar as these are known or can be estimated at any time. (3) Analysis should be able to respond to engineering and management needs for quantitative evaluation of system design. (4) Access to results from fully developed analysis models should be timely (a few days) and economi- cal. (5) The output results of analytic models must be readily interpreted into usual system engineering 192 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 descriptive parameters, such as throughput times, element availability, and facility utilization. III. Operations Analysis Approach In order to meet the objective, it was decided to use the General Purpose Simulation System (GPSS) application program as the central tool in the operations analysis. The reasons for this choice include: (1) GPSS is a developed, available user applications program. (2) Extensive past experience with GPSS is available in the system support group. (3) GPSS, in its organization and design, is directly suited to the detailed analysis of traffic-flow systems having discrete traffic units. (4) Use of a powerful and versatile montecarlo system allows effective automation of operations analysis, minimizing the amount of analytic modeling requir- ing other methods. Because the Network systems, the data records produc- tion, and the systems functional design and specification were at a fairly advanced state, it was anticipated that the requisite specification for quantitative modeling, at a useful level of detail, would be available, thereby shortening that part of the simulation model task which is generally the most consuming of resources; this hope was happily confirmed. GPSS, in its structure, permits modular development of the elements which will ultimately comprise a model. This feature was used to advantage to develop the various elements which constitute a final model of the overall data records production processes. Furthermore, care has been taken to preserve modularity in the end-product simula- tion models, thereby increasing model structure generality such that variations in specification or modification of configuration or functional design can be incorporated into production analysis models relatively quickly. The remaining sections of this report describe the configurations and functional design of the system, the details of model assumptions and specification, and the quantitative results yielded by these simulation models. IV. Requirements of the Analysis Approach Because development of the system models themselves "simulates" the design and implementation of a function- ing system, the requirements which the analyst must meet are the following: (1) System block diagram. This provides a general "map" of traffic flow from initiation to destination, as well as a general indication of the boundaries of functional independence within the overall system (the "blocks"). (2) Description and diagrams of the functional logic of each element of the system. This must be provided to the level of detail which is comparable with system status and interactions which have a signifi- cant effect upon the observable measures of traffic flow. (3) System and functional element specification. This includes primarily the quantitative specification of processes and events which affect traffic flow, such as traffic density, element capacities, reliability statistics, process times, and priorities. (4) Description of the system dynamic "drivers." A profile of the input dynamic flow, including descrip- tion of all associated parameters which distinguish traffic types in significant ways in the functional operation. These requirements have been met sufficiently to produce the operating models described here. The sources for these requirements are the documents mentioned at the beginning of the memorandum. Because of these relatively demanding requirements, the initiation of system simulation efforts early in the functional design process often is useful in identifying areas where design details are poorly understood, require more specific attention, or where conflicts and ambiguities exist. V. Brief Description of the System Figure 1 depicts graphically the data record flow system, from input to output, which is the subject of the analysis models. The modules of the computer simulation models correspond with the major elements of the system, shown as blocks in the diagram. The basic unit of traffic considered is the data block, so that the dynamic units "flowing" in the simulation models provide for events and model bookkeeping at the data block level (although each dynamic entity during simulation generally represents a collection of data blocks, the objective being economy of required computing without sacrifice of mode validity or flexibility). The first level of distinction among data flow types, introduced at the input, is the triple specification: JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 193 mission, deep space station source, and high-speed or wideband type. VI. Brief Description of the Models There is currently available for analysis purposes one basic model of the data flow and data records production in the Network for the Viking era. Two versions of this model exist and have been used to generate numerical results: one version provides for 4 tape-drive units at the Merge Processor (Model A); the other provides for 8 tape- drive units (Model B), a network configuration design which arose while Model A was being developed. The simulation models are modular in structure, with logic modules and their associated assumptions and attributes as, follows: (1) DSS Module. Routes real-time data pass representa- tives to the Comm Log Processor module, and creates a digital original data record representative for records bookkeeping and later coordination with recall activity. Assumes existence of a single-thread, serial facility which is not interrupted by ancillary activity (such as recall) during real-time pass activity. Any particular complement of DSSs, providing mission support during a time-span of interest, may be represented in the models. (2) Comm Log Processor Module. Provides two basic model functions: network data log (NDL) coordina- tion and bookkeeping, and generation of gap statistics to be associated with each data stream representative. This module is subdivided into three submodules which provide the necessary logical structure: (a) High-Speed (HS) Data NDL Module. Generates NDL representatives and performs the book- keeping which assigns to each representative a unique identifier and the number of passes associated with it. The current models assume NDLs are recorded according to a fixed schedule which is coordinated with pass support. (b) High-Speed Data Module. Associates with each high-speed data stream representative the identi- fiers of the NDLs which are active during the pass period, and the gap statistics generated for each particular pass. (c) Wideband Data Module. Associates with each wideband (WB) data stream representative the number of NDL tapes generated during the pass, and gap statistics for the data stream. (3) Network Data Log Transfer Logic. Provides for direct transfer of NDLs to the Merge Processor, except in the case of Real-Time Monitor outage during production, in which case NDLs are first captured to fill-in the RTM outage, and then transferred to the Merge Processor. Allowance for RTM needs so far affects only the HS data streams in the models, since the precise effect on WB streams was unknown to the author. Wideband logs are therefore transferred directly to the Merge Proces- sor at the end-of-pass. (4) Gap Edit and Recall Request Module. Receives the data stream representatives after the pass, for both wideband and high-speed data. Simulates any additional time required for Cap Lists to be turned over from the monitor (there is currently no active module for monitor subsystems, since it is assumed that monitor does not impinge directly on the data records throughput except in the two ways men- tioned). Simulates the process time required to generate edited gap lists and data recall requests. Priority is then assigned the data stream representa- tives to give data recall activity priority over intermediate data record (IDR) merge processing in competition for facilities at the Merge Processor. The data stream representatives become "recall request" representatives as they pass into the Merge Processor job sequencing chain at this point. A Gap Editor Availability module is associated with the Gap Edit module to represent intervals during each simulated day when the edit operator is not available, and edit jobs which become active or are waiting at these times are further delayed until the edit operator resumes activity. (5) Merge Processor Module. Provides for the logical control and simulation of recall data tape production and data merge for IDR production. In order to accomplish these functions, the module is parti- tioned into several logical units: (a) Recall Chain. Receives any entering recall task which must wait for available facilities. Strict control of task sequencing is maintained by use of a "chain" entity. Recall tasks have priority over merge tasks. Within the recall class, the order is first-in first-out. (b) IDR Chain. Receives merge tasks which must wait for facilities. Ordering within the merge class is first-in first-out. (c) Three additional chain entities, NDL, Merge, and Temp, provide ordering and flow control for 194 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 HS NDL representative transactions at the Merge Processor. (d) Tape-drive unit facilities represent "single- thread" operation of the tape drives in both models. Jobs awaiting facility availability on the Recall or IDR chains will wait until sufficient tape-drive facilities are available before proceed- ing to execute task simulation at the Merge Processor. (6) Reliability/Availability Modules. In addition to the Cap Editor availability module, there are also present in the current models reliability simulation modules for Real-Time Monitor (insofar as the flow of NDLs is affected), Merge Processor, and Merge Processor Tape-Drive Units. VII. Description of the Dynamic Drivers The discrete dynamic entities in GPSS models are referred to as "transactions." Transactions, which simulate the traffic units in a dynamic traffic-flow simulation, may be assigned and carry with them various parametric values of significance to the particular model. In this model, three classes of transactions are generated as the dynamic system drivers: (1) Data pass representative transactions. (2) HS data NDL transactions. (3) Drivers for the various unreliability/availability modules. VIII. Data Pass Representatives The models are designed to allow for an arbitrary number of DSS-mission-data type generators. The current models incorporate 14 distinct "data pass" representatives of this type. The module which generates these dynamic entities associates with them: (1) Pass start time. (2) Pass duration. (3) DSS identifier. (4) Project identifier. (5) Data type identifier (high speed or wideband). (6) Data rate for telemetry stream represented. Each pass generator may initiate passes according to a predetermined and specified view period profile. In the current versions, a simple, fixed view period profile is assumed wherein each pass for a particular stream has a fixed duration and successive passes begin 24 hours after the beginning of the next preceding pass, for the whole interval simulated. All these simplifying assumptions may be relaxed in order to incorporate more realistic view period profiles, if there are cases in which these parameters have a significant effect upon the outcome. Table 1 summarizes the complement of telemetry data streams represented in the current models. The simulator clock unit is minute. The profile models are designed to represent a "worst case" support load during Viking encounter. Time can be simulated continuously in any model run up to 90 days. Driver profiles may be constructed to simulate support schedules and data profiles which change over time. IX. High-Speed Data Network Data Log Representatives The production of wideband data network data logs (NDLs) at the Comm Log Processor appears to be heavily dependent upon each WB data pass, since, otherwise, none are produced. Therefore, it is not necessary to simulate a separate NDL entity flow; all necessary information can be carried along by each WB data pass transaction. High-speed data NDLs, on the other hand, may be produced successively according to a schedule which is not dominated by any single data pass considera- tion; because of this essential "pass-independence," the HS NDLs must be represented as separate model entities. The NDL module generates a sequence of contiguous NDLs according to a specified schedule. The NDLs and the HS data passes which should be associated with them (i.e., passes which are actively yielding HS data during the recording time of the NDL) are mutually coordinated in the model by cross-indexing the NDL identifiers to associated data pass transactions. Beginning at model "epoch," the HS NDLs have record times of 7, 9, and 8 hours, in succession, a sequence which is periodic throughout model runs. Since data passes and HS NDL cycles are periodic with periods of 24 hours, the NDL cycle has been chosen to yield a convenient recording schedule. Figure 2 shows graphically the association between HS NDLs and telemetry stream data passes recorded on them. The HS NDLs pass from active "recording" status to: (1) Merge Processor to await IDR production for each of the data streams associated, or (2) The "Real-Time Monitor (RTM)-System Perform- ance Record (SPR) fill-in" model if an RTM outage JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 195 has occurred during the active time of the NDL, then to (1). X. Drivers for Unavailability Modules Each reliability or availability module in the models generates its own independent dynamic event driver. The event driver controls failure event initiation (or other facility unavailability) for its particular associated system element. It also controls the associated down-time for each of these events. Both the intervals between outage and outage duration are sampled according to analyst-specified distributions. Table 2 summarizes the various down-time and unavailability events associated with the current models. XI. General Model Assumptions and Model Specification A. General Assumptions and Model Features (1) Telemetry data streams, including post-pass recall, are simulated according to the system-driver time table and rates given in Table 1. These streams and their interactions with the functional systems are the most directly related to the throughput times for IDR production. Monitor, command, and metric data streams are not specifically simulated as distinct dynamic entities, but are maintained as a cumulative traffic composite in order to be accounted for in the production of HS data IDRs. (2) Recall play-back begins after the real-time pass (reference documents indicate that this is a valid assumption). (3) Recall tape production has priority over IDR merge processing. (4) For each data pass, the merge process may begin only when all associated NDLs and the Recall Data tape are available at the Merge Processor job sequence chains. (5) Each of the distinct data passes represented is associated one-to-one with production of a separate IDR. B. Model Specification (1) Input data specification for the data passes has been described above. (2) Gap simulation for wideband data streams (all). (a) Time between gaps: Poisson distributed with mean 1 gap/414 seconds. (b) Gap length: Poisson distributed with mean 10 wideband data blocks (WBDB)/gap. Result will be: expected number of gaps in 12 hours = 104; expected number of blocks lost = 1040, each 12-hour pass. (3) Gap simulation for high-speed data streams (all). (a) Time between gaps: Poisson, with mean 1 gap/ 800 seconds. (b) Gap length (in high-speed data blocks HSDB): Poisson, with mean 2 HSDB/gap, Result: ex- pected number of gaps in 12 hours = 54; expected number of blocks lost = 108, each 12- hour pass. These statistical parameters for HS data are hypothetical. For the 11 data streams included, these statistics yield a weighted aver- age 0.75% recoverable data loss over all streams (99.25% of HSDB received at Comm Log Processor in real-time, ignoring nonrecoverable losses). The data quality statistics for the simulation are summarized in Table 3. (4) Numbers of data blocks recorded per Digital Original Data Record (DODR): (a) High-speed DODR: 85140 HSDB (b) Wideband DODR: 54750 WBDB (5) SPR "outages" (Model is not based on quantitative data, since none are available; the only statement in the reference documents claims that outage is a "fairly infrequent event"): (a) Time to failure: Poisson, with mean 360 hours (15 days). (b) Times to recover: Uniform on [13, 17] minutes (average: 15 minutes). (6) Gap list edit time. Computed as the sum of: (a) 0.2 minutes per gap. (b) "Variability" factor, uniformly distributed on [0, 0.05 X (number of gaps)]; with mean 0.025 X (number of gaps) minutes. (c) Typical values for edit times: for 50 gaps, 11.25 minutes; for 100 gaps, 22.5 minutes. (7) Time to recall data from DSS (assuming facilities at both ends are acquired and ready): (a) 15 ± 5 minutes "set-up" time (uniform on [10, 20]). (b) 8 minutes read time per DODR. (c) 2.4 minutes rewind time per DODR. 196 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 (d) 2 ± 1 minute "tape handling" time per DODR (uniform on [1, 3]). Table 4 contains average recall times for all characteristic data streams. (8) Wideband data pass merge process time: (a) Number NDLs per pass: (number WBDB)/ 79660. (b) Read time per NDL: 7.27 min. (c) Rewind time per NDL: 2.4 min. (d) Tape handling time: 2. min. (e) Write time. Assumes 11616 Logical Data Rec- ords (LDRs) per IDR tape (11616 X 5 WBDB/ LDR = 58080 WBDB/IDR tape). Write rate: 0.0356 sec/LDR, 6.9 min/IDR. Typical merge process times which result: DSS 14: 334 minutes (5 hours 34 minutes). DSS 43 and 63: 225 minutes (3 hours 45 minutes). (9) High-speed data pass merge process time: (a) Read time per NDL: 7.27 min. (b) Rewind time per NDL: 2.4 min. (c) Tape handling time: 2 min. These factors are applied to the number of NDLs on which the HS data for the particular pass are written; (a) and (b) should apply to the actual (fractional) number, and (c) applies to the integral number of tapes represented. In the case of HS NDLs, HS data pass terminations generally do not coincide with the end of the last NDL written upon. For the model, it was found that an average (over all data passes) fraction of NDL not read (after pass termination) is about 0.125 of the total NDL time. Therefore, a compensating factor has been incorpo- rated into the general formula used to compute HS merge times, so that (a) and (b) become 0.94 X 7.27 min and 0.94 X 2.4 min, respectively. (d) Write time: 0.02315 sec X number (LDRs). (e) Rewind: 2.4 min X number (IDRs). (f) Tape handling: 3 min X number (LDRs) where: Number (LDRs) = (total HSDBs)/5 Number (IDRs) = (total HSDBs)/93430. Some typical HSD merge process times which result are: DSS 11: 32 min. DSS 12: 28.4 min. DSS 14(A): 33 min. In case Network Operations Control Center (NOCC) were required to verify the computer compatibility of written IDR tapes, it is assumed that verification would be performed at the Merge Processor as a sequential part of the IDR production operation. The verification process model assumed by the analyst is: read IDR tapes, rewind IDR tapes. A separate simulation model version was created which includes the verification process, the addi- tional process times having been specified as follows: (10) Wideband IDR verification: (a) Read-to-verify: 0.03565 sec per LDR. (b) Rewind: 2.4 min per IDR tape. (c) Tape handling: 3 min per IDR tape. Verify times computed by these formulas are: DSS 14: 140 min. DSS 43 and 63: 94 min. (11) High-speed IDR verification: (a) Read-to-verify: 0.02315 sec per LDR. (b) Rewind: 2.4 min per IDR (or fraction). (c) Tape handling: 2 min per IDR tape. (12) Job sequence policy at Merge Processor: (a) Recall tape processing has priority over merge processing; i.e., if there are any recall jobs waiting on the job chain, they will always take precedence over merge processing. (b) Within the two priority classes, jobs are se- quenced according to oldest waiting job first. The performance at the Merge Processor, compared with facility utilization and requirement to produce IDRs within 24 hours from end-of-pass, is essentially dependent upon the job sequencing policy. Nearly any quantifiable policy could be implemented as a policy model. As of this writing, no attempt has been made to incorporate modified sequencing policies into the model runs. XII. Simulation Results Simulation runs have been made with both basic versions of the Automatic Total Recall System/IDR models, i.e., Model A having 4 tape-drive units, and Model JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 197 B, having 8 tape-drive units. These simulation runs have simulated 3 and 10 days support to IDR production, using the mission profile defined in a previous section. These results are tabulated in Tables 5 and 6. Other cases have been simulated, especially cases which include variable mission data profiles. These data are not included here, however, since they would not add anything significant to this summary. Model output data in Table 5 show that the Merge Processor with 4 tape-drive units available for input/ output (I/O) operations can perform within the network requirement for finished IDRs within 24 hours of end-of- pass. Obviously these results are qualified by the validity of the assumptions used (and described in a previous section). Model output statistics show the tape-drive utilization factors to be relatively high, the implication being that, in order to perform to requirement, it is necessary that a very tight control be maintained on the job sequencing schedule for 24 hours each day that such a support level is required. Furthermore, the reader is reminded that, although the model support profile may be a realistic "worst case," other model features to which throughput time is quite sensitive may be lenient; e.g., no consideration for possible wait on communications link outages, etc. These features are easily modified in the models, should there be data available to indicate that further analysis would be of some value. Therefore, it is hoped that the reader may give serious consideration to the validity of the model parametric specification. Table 6 shows that a Merge Processor facility with 8 tape-drive units handles the load of the support profile rather easily (although model output "bookkeeping" statistics indicate that all eight units would be in use on occasion, if the job-sequencing policy were to process jobs as soon as they enter the facility, and I/O units are available). A significant feature of the 8 tape-drive version is that it permits two simultaneous, independent merge process jobs to be done, with margin to handle one or two recall jobs. The 4 tape-drive version is strictly limited to "single- thread" merge processing. A further analytic result which may be of some operational significance is that, on the 8 tape-drive version, no recall job waits on queue for I/O facilities, whereas, on the 4 tape-drive version, as many as three recall jobs may wait on queue at some time before I/O facilities are available for acquiring recalled data. With the further requirement for IDR compatibility verification imposed upon the Merge Processor, under the quantitative assumptions made for verification processing times, the 4 tape-drive unit Merge Processor is no longer able to perform adequately to the 24-hour throughput requirement. The results are summarized in Table 7. Furthermore, additional model statistical output shows that I/O facilities used for merge processing (as well as recall) have a joint utilization factor over 0.92, a situation which indicates that the process is unstable and that, therefore, throughput becomes worse with increasing time. The 8 tape-drive Merge Processor, with the additional burden of verification of IDR tapes, still meets the 24-hour requirement without difficulty; furthermore, the process remains quite stable. The throughput time statistics for 10 days simulated passes are displayed in Table 8. Within the limitations of the initial model assumptions which have been adopted for this study and demonstra- tion, it may be concluded that: (1) Without the burden of IDR verification, the 4 tape- drive configuration Merge Processor would likely perform within the 24-hour throughput bound. (2) With verification as an additional requirement, the 4 tape-drive-equipped processor is not capable of meeting requirements adequately. (3) The 8 tape-drive configuration will meet the throughput requirement under all conditions consid- ered thus far. 198 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 1. Specification of model DSS data streams DSS" DSS 11 DSS 12 DSS 14 (W) DSS 14 (A) DSS 14(B) DSS 42 DSS 43 (W) DSS43(H) DSS 44 DSS 61 DSS 62 DSS63(\V) DSS63(A) DSS63(B) Data stream supported Viking Orbiter (VO) Engr Pioneer (PIO) VO Sci VO Engr Viking Lander (V'L) Sci + Engr VO Engr VO Sci VO Engr PIO VO Engr PIO VO Sci VO Engr VL Sci & Engr Telemetry data rate, blocks/min 12 20 900 24 67 12 600 12 20 12 20 600 24 67 • (W) is designator for wideband data channel; ( A ) , (B ) , Data type ( H S o r W B ) HS HS WB HS HS HS WB HS HS HS HS WB HS HS and (H) are Additional data rate (MOM, TRK, CMD), (blocks/min) 59 17 0 59 14 59 0 59 17 59 17 0 59 14 designators for Initial pass epoch13 0 1110 0 0 30 450 450 4.50 270 990 540 990 990 30 high-speed data Pass duration, min 720 660 720 720 180 720 720 720 360 690 660 690 690 180 channels. Time between passes, min 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 bRelative to simulated clock time, in minutes. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 199 Table 2. Time table of events which compete for facility availability Model facility Real-Time Monitor Gap Edit Operator Merge Processor Tape-drive units ( for 4 units ) ( for 8 units ) Event Monitor outage Downtime (at outage) Edit Operator "out" Processor failure Drive unit failure ( each unit ) Mean Mean time duration, to event min 15 days 15 4 hours 20 10 days 20 40 days 15 80 days 15 (each unit) Model facility availability 0.9993 0.923 0.9986 0.999 (facility) 0.999 ( facility ) Table 4. Expected recall times for high-speed and wideband data streams Expected DSS" Number DODRs Datatype recall time, min 11, 12,14 (A), 14 ( B ) , 42,43 ( H ) , 1 HS 25.9 61, 62, 63 ( A ) , (for all HS passes) 63 (B) 14 (W) 12 WB 167.8 43 (W) 8 WB 116.2 63 (W) "(A) , (B) , and (H) are designators for high-speed channels; (W) is designator for wideband data channel. Table 5. Throughput time statistics to completed IDR: Model "A" (4 tape-drive units at Merge Processor) 3- and 10-day pass support simulated Table 3. High-speed data loss during real-time operations DSS» (recoverable science and engineering telemetry)" DSS" DSS 11 DSS 12 DSS 14(A) DSS 14(B) DSS 42 DSS43(H) DSS 44 DSS 61 DSS 62 DSS63(A) DSS63(B) Pass dura- tion, min 720 660 720 180 720 720 360 690 660 690 180 Telem- etry data rate, blocks/ min 12 20 24 67 12 12 20 12 20 24 67 Total telemetry data blocks per pass 8640 13200 17280 12060 8640 8640 7200 8280 13200 16560 12060 Blocks lost (avg) ( recover- able) 108 99 108 27 108 108 54 104 99 104 27 Comm quality ratio 0.9875 0.9925 0.9938 0.9978 0.9875 0.9875 0.9925 0.9875 0.9925 0.9938 0.9978 DSS 11 DSS 12 DSS 14 (W) DSS 14 (A) DSS 14 (B) DSS 42 DSS 43 (W) DSS 43 ( H ) DSS 44 DSS 61 DSS 62 DSS 63 (W) DSS 63 (A) DSS 63 ( B ) Number of passes6 Mean Standard throughput deviation, time, hours hours 3 days 10 days 3 days 3 3 3 3 3 3 3 3 3 3 3 3 3 3 10 10 10 10 10 10 10 10 10 10 10 10 10 10 11.00 5.00 9.67 12.67 5.00 8.67 7.67 9.00 12.00 6.00 8.67 8.67 5.67 4.33 10 days 3 days 10 days 10.3 0 6.4 1.41 10.0 0.47 10.9 1.70 6.6 0 9.0 0.47 7.9 0.47 9.0 0 11.0 0 7.3 1.41 9.0 0.47 7.7 1.25 7.1 0.94 6.5 0.47 a(A), (B), and (H) are designators for high-speed data nels; (W) is designator bProfile generator starts,i r . i i for wideband at time 0, on 1 data channel. a "blank" system; 1.73 1.63 0.77 2.47 1.56 0.45 0.30 0.45 2.00 1.62 0.63 1.35 1.37 1.69 chan- at the "Weighted average data quality over all HS streams: 0.9925. b( A), (B) , and (H) are designators for high-speed data channels. end ot three and ten days, respectively, the pass generator is "turned off" and the simulated systems complete tasks remaining without additional loading. 200 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Table 6. Throughput time statistics to completed IDR: Model "B" (8 tape-drive units at Merge Processor) 3- and 10-day pass support simulated DSS" Number of passes'1 3 days DSS 11 DSS 12 DSS 14 (W) DSS 14 (A) DSS 14 (B) DSS 42 DSS 43 (W) DSS 43 ( H ) DSS 44 DSS 61 DSS 62 DSS 63 (W) DSS 63 ( A ) DSS 63 (B) 3 3 3 3 3 3 3 3 3 3 3 3 3 3 10 days 10 10 10 10 10 10 10 10 10 10 10 10 10 10 Mean throughput time, hours 3 days 6.00 4.00 9.67 6.00 4.67 6.33 7.00 6.00 7.00 5.00 6.00 7.00 4.67 4.33 10 days 5.7 4.0 9.8 5.6 4.6 6.2 7.0 6.0 6.5 4.9 6.0 6.9 5.0 4.6 Standard deviation, hours 3 days 0 0 0.47 0 0.47 0.47 0 0 0 0 0 0 0.47 0.47 10 days 0.90 0 0.40 1.20 0.49 0.40 0 0 1.50 0.30 0 0.30 0 0.49 "See footnote a, Table 5. ''See footnote b, Table 5. Table 7. Throughput time statistics for IDR: Model "A" with verification processing 10-day support simulated Number DSS" of IDRs" completed DSS 11 DSS 12 DSS 14 (W) DSS 14 (A) DSS 14 (B) DSS 42 DSS 43 (W) DSS 43 (H) DSS 44 DSS 61 DSS 62 DSS 63 (W) DSS 63 (A) DSS 63 (B) 10 9 10 10 10 10 10 10 10 10 10 9 9 10 Mean throughput time, hours 12.20 15.44 19.20 12.40 11.10 14.60 18.50 15.10 12.50 14.70 18.20 16.78 14.44 11.10 Standard deviation, hours 3.89 4.19 3.99 3.53 3.48 4.80 3.75 5.01 3.59 4.67 3.92 3.85 4.79 3.70 Range of throughput times, hours 6-18 10-21 12-25 7-17 5-16 7-23 12-23 8-24 7-17 8-22 13-24 9-21 8-22 4-16 Table 8. Throughput time statistics for IDR: Model "B" with verification 10-day pass support simulated DSS" DSS 11 DSS 12 DSS 14 (W) DSS 14 (A) DSS 14 (B) DSS 42 DSS 43 (W) DSS 43 (H) DSS 44 DSS 61 DSS 62 DSS 63 ( W ) DSS 63 (A) DSS 63 (B) "See footnote bSee footnote Number of IDRs" completed 10 10 10 10 10 10 10 10 10 10 10 10 10 10 a, Table 5. b, Table 5. Mean throughput time, hours 5.9 4.9 12.1 6.3 4.8 6.5 8.7 6.5 6.6 5.3 6.8 8.5 5.5 4.7 Standard deviation, hours 1.04 0.30 0.30 1.49 0.40 0.50 0.46 0.50 1.20 0.64 0.40 0.50 0.50 0.46 Range of throughput times, hours 3-7 4-5 12-13 2-7 4-5 6-7 8-9 6-7 3-7 4-6 6-7 8-9 5-6 4-5 "See footnote a, Table 5. ''See footnote b, Table 5. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 201 WB DATA STREAMS HS DATA STREAMS (INCL POST-PASS P/B) Fig. 1. Network data records block diagram 202 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 END-OF-PA55 (ALL DSS/DATA STREAM PASSES) TIME; 10-min AVERAGE GAP EDIT TIME AVERAGE: 0.225 x (NUMBER OF GAPS ) min QLAG TIME; 5-min AVERAGE RECALL TIME AVERAGE: 13 + 1.5 x (NUMBER DODR TAPES) +11.4 X (FRACTIONAL NUMBER DODRs) min (LAG TIME; io-mm AVERAGE NDL AND FACILITY AVAILABILITY MERGE TIME AVERAGE { HS: 11WB:0. .0 x (NUMBER NDU) +0.000135 (HSDB) + 3 min000505 (WBDB) + 7 min Fig. 2. Flow sequence to IDR production JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 203 DSS 11 VOENGR-C DSS 14 (A) VOENGR - 1 inss 14 rm- VI I (DSS 12 1 DSS 44 PI 1 (DSS 61 ) J(DSS 63A) 1 Inss A3 fRWl ps , 3bps , , DSS 61 VO ENGR - 33 1/3 bps Sbps , ( DSS 63 (A) VOENGR 33 1/3 X 2 bps i 1 , 1 , 1 , 1 1600 1800 2000 2200 0000 0200 0400 0600 0800 1000 1200 1400 1600 8/12/76 8/13/76 Fig. 3. High-speed data passes and high-speed data NDL (telemetry data) 204 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Coordinate Measuring Machine and Programmable Calculator H. A. Greth and J. Kundrat Quality Assurance DSN and Mechanical Hardware Section Quality Assurance Mechanical Inspection, anticipating the need for improved measuring techniques for the various Laboratory programs, has purchased a Coordinate Measuring Machine which has the capability of significantly reducing inspection time while increasing reliability. I. Introduction It was necessary for JPL Quality Assurance to find improved methods of performing inspections with speed and reliability. Commercially available equipment would have to meet the following criteria: (1) Expand measurement capabilities. (2) Reduce set-up time (man-hours). (3) Increase speed and accuracy. (4) Have English (inch)/metric display and printout capabilities. The Coordinate Measuring Machine, equipped with a programmable calculator, expands measuring capabilities and, in place of time-consuming manual recording and calculations, instantly computes and prints out measure- ments. II. Description of Equipment The Coordinate Measuring Machine (Fig. 1) is a three- axis X,Y,Z measuring device. Each axis is provided with bronze air bearings which allow all measuring axes a frictionless noncontact movement, assuring a deflection- free measurement. The measuring system employs a principle of reading fluctuations of light intensities through photocells. These photocells pick up the changes in intensities which are 90 deg out of phase. Then, through electronic circuitry, these measurements are digitally displayed in either English or metric. A feature of the machine is the touch trigger probe. This probe is an omnidirectional electronic null-sensing device with a repeatability of 1.0 fim (0.00005 in.) and feather-touch sensitivity of 0.04 N (4 g). The touch trigger probe, for example, with a contact point having a right angle bend, could be used to check in any direction the JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 205 depth and height of internal grooves or bores having stepped diameters. The programmable calculator (Fig. 2) is the heart of the Coordinate Measuring Machine and uses a pre-program- med cartridge tape to perform operations previously requiring the use of a computer. It has a 12-digit readout display and a hard copy printer which permanently records all measurements. A choice of measuring systems (Cartesian or Polar) is provided, and single-point or multipoint measuring methods (Fig. 3) may be programmed. The Cartesian System is for determining the location of a point in relation to two straight lines. This is frequently used in box-type rectangular dimensioning. The Polar Coordinate System determines the location of a point in relation to its radius vector from a fixed origin. Polar coordinates are frequently used for measuring bolt holes and circles. The single-point method is for measuring the center distance between patterns with a tapered probe or a ball probe, or for measuring along the edge of a part. Multipoint methods are used for measuring hole diameters and determining the center by measuring points on the wall of the hole with a ball probe. All desired information is provided by the calculator. An important feature is automatic alignment, which compensates for misalignment between the workpiece on the measuring table and the measurement axes by calculating a correction factor and applying that factor to the measurements taken. Specifications Resolution: 0.002 mm or 0.0001 in. Measurement accuracy: ±0.012 mm or ±0.0005 in. Repeatability: ±0.005 mm or ±0.0002 in. Work table: Solid black granite with stainless steel thread inserts Bearings: Frictionless air bearings (open adjustable type) Measuring range: X 685 mm or 27 in.; Y 508 mm or 20 in.; Z 457 mm or 18 in. III. Previous Test Methods Versus Coordinate Measuring Machine Previously used methods of inspecting hardware were generally confined to the use of height gages, dial indicators, and depth gages. These instruments were used to measure such parameters as roundness, flatness, true position, etc. The hand method of measurements is slow and subject to human error. The Coordinate Measuring Machine can be program- med to handle parameters of true position, roundness, and flatness. The following are examples of calculator mea- surement programs: Example 1 (Fig. 4) illustrates a program which measures the center in polar coordinates and the diameter of holes and bosses using the multipoint method with ball probe which permits use of automatic alignment. Measure- ments are taken in any of three planes, with a printout of radius angle, diameter of holes, and X,Y dimensions. Example 2 (Fig. 5) illustrates a program which measures the concentricity of two features, with the second feature taken at maximum material condition (MMC). The multipoint method using a ball probe for measurements and deviations is expressed as a diameter or total indicator reading (TIR). The printout shows concentricity limit as a tolerance, with deviations of out-of-tolerance conditions. Example 3 (Fig. 6) illustrates a program which measures the roundness of a feature, holes or bosses, and inside or outside radii, using the multipoint method. Example 4 (Fig. 7) illustrates a program which measures true position regardless of feature size, using the Cartesian Coordinate System. If the diameter being measured does not lie within the prescribed diameter tolerance, the closer deviation limit is used in the true position calculation. Example 5 (Fig. 8) illustrates a program which measures a pattern generation. This program, having axis starting point and axis spacing with the offset angle along each axis, is all that is required to generate a rectangular or circular pattern. 206 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 IV. Summary When dealing with a number of parts having many critical tolerances, the hand method is very time- consuming, and very often costly attachments are needed to perform the inspection required. By using the Coordinate Measuring Machine with calculator and touch trigger probe, hardware is inspected quickly and accu- rately, with all measurements automatically printed out for a complete record of dimensions. This machine is definitely cost-effective and reduces Quality Assurance costs in the following ways: (1) It increases inspection productivity by a factor of three to one (as compared to the conventional surface plate, height gage, and indicator method). (2) Its use requires no special tooling (eliminates the cost of jigs and fixtures). (3) It eliminates human error. Problems that are inherent in transcribing data manually are nonexis- tent and thus inspection down time is reduced. Bibliography Validator 50 Manual, Brown & Sharpe Manufacturing Co., North Kingstown, R. I., June 15, 1974. "Computer Capabilities," Fact Sheet Val-CC, Brown & Sharpe, North Kingstown, R.I. "Val-Calculator," by Textronix, Fact Sheet Val-Cal, Brown & Sharpe, North Kingstown, R. I. JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 207 Fig. 1. Coordinate measuring system 208 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Fig. 2. Programmable Val-Calculator JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 209 MEASURED I DISTANCE X ;[POINT r~ MEASURED DISTANCE I LOCATION r f _1 X-AXIS CARTESIAN SYSTEM POINT LOCATION FIXED ORIGIN POLAR COORDINATE SYSTEM SINGLE-POINT METHOD MULTIPOINT METHOD Fig. 3. Single-point and multipoint measuring methods Fig. 4. Three-plane measurement CONCENTRICITY ~] 1 - ECCENTRICITY Fig. 5. Concentricity measurement 210 JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 Fig. 6. Roundness measurement Fig. 7. True position measurement •X SPACING Y SPACING STARTING POINT OFFSET ANGLE Fig. 8. Pattern generation measurement JPL DEEP SPACE NETWORK PROGRESS REPORT 42-29 N A S A - J P l - Coml , L.A.. Calif. 211

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