Helicopter Flight Test of 3-D Imaging Flash LIDAR Technology for Safe, Autonomous, and Precise Planetary Landing

Two flash lidars, integrated from a number of cutting-edge components from industry and NASA, are lab characterized and flight tested for determination of maximum operational range under the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project (in its fourth development and field test cycle) which is seeking to develop a guidance, navigation, and control (GN&C) and sensing system based on lidar technology capable of enabling safe, precise crewed or robotic landings in challenging terrain on planetary bodies under any ambient lighting conditions. The flash lidars incorporate pioneering 3-D imaging cameras based on Indium-Gallium-Arsenide Avalanche Photo Diode (InGaAs APD) and novel micro-electronic technology for a 128 x 128 pixel array operating at 30 Hz, high pulse-energy 1.06 micrometer Nd:YAG lasers, and high performance transmitter and receiver fixed and zoom optics. The two flash lidars are characterized on the NASA-Langley Research Center (LaRC) Sensor Test Range, integrated with other portions of the ALHAT GN&C system from partner organizations into an instrument pod at NASA-JPL, integrated onto an Erickson Aircrane Helicopter at NASA-Dryden, and flight tested at the Edwards AFB Rogers dry lakebed over a field of human-made geometric hazards during the summer of 2010. Results show that the maximum operational range goal of 1 km is met and exceeded up to a value of 1.2 km. In addition, calibrated 3-D images of several hazards are acquired in real-time for later reconstruction into Digital Elevation Maps (DEM's)

Mariner IV Mission to Mars. Part I

This technical report is a series of individual papers documenting the Mariner-Mars project from its beginning in 1962 following the successful Mariner-Venus mission. Part I is pre-encounter data. It includes papers on the design, development, and testing of Mariner IV, as well as papers detailing methods of maintaining communication with and obtaining data from the spacecraft during flight, and expected results during encounter with Mars. Part 11, post-encounter data, to be published later, will consist of documentation of the events taking place during Mariner IV's encounter with Mars and thereafter. The Mariner-Mars mission, the culmination of an era of spacecraft development, has contributed much new technology to be used in future projects

RADAR Based Collision Avoidance for Unmanned Aircraft Systems

Unmanned Aircraft Systems (UAS) have become increasingly prevalent and will represent an increasing percentage of all aviation. These unmanned aircraft are available in a wide range of sizes and capabilities and can be used for a multitude of civilian and military applications. However, as the number of UAS increases so does the risk of mid-air collisions involving unmanned aircraft. This dissertation aims present one possible solution for addressing the mid-air collision problem in addition to increasing the levels of autonomy of UAS beyond waypoint navigation to include preemptive sensor-based collision avoidance. The presented research goes beyond the current state of the art by demonstrating the feasibility and providing an example of a scalable, self-contained, RADAR-based, collision avoidance system. The technology described herein can be made suitable for use on a miniature (Maximum Takeoff Weight \u3c 10kg) UAS platform. This is of paramount importance as the miniature UAS field has the lowest barriers to entry (acquisition and operating costs) and consequently represents the most rapidly increasing class of UAS

Performance analysis and algorithm enhancement of feature-aided-tracker (FAT) simulation software using 1-D high-range-resolution (HRR) radar signature profiles

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.Includes bibliographical references (p. 94).The current Lincoln Laboratory (LL) MATLAB Feature-Aided-Tracker (FAT) software was adjusted and appended to provide a robust ground-target radar tracking simulation tool. It utilizes algorithms from the LL UAV Radar Moving Target Tracker (1991) and the LL FAT Tracking Software (2002). One-dimensional High-Range-Resolution (HRR) radar signature target profiles were used to assist in track-to-report data association through classification-aided and signature-aided tracking (CAT and SAT) algorithms. Profiles were obtained from the DARPA-sponsored Moving Target Feature Phenomenology (MTFP) program. Performance Analysis of this simulation tool reinforced the hypothesis that target aspect angle error estimation (state estimation) drives the performance of CAT, SAT, and Kinematic Tracking (KT) algorithms. A decaying exponential relationship exists between the Kalman filter estimate of target-speed and expected aspect angle error. This relationship was exploited to optimize the allocation of computational resources while enlarging the database aspect angle search in CAT to improve performance. Vehicle classification accuracy is improved by 70% and data association accuracy is improved by 12% in kinematically ambiguous situations such as when target intersections occur. SAT was improved 3% using this knowledge. Additionally, the target report HRR profile from each scan was used to generate an "On-The- Fly" SAT HRR profile database. This algorithm tests the similarity between the current target report HRR profile and the database HRR profiles. If there is sufficient resemblance, the report HRR is added to the database; if not, the database is reset.(cont.) This information can be employed to provide up to a 9% performance improvement over the previous version of SAT in a best-case scenario. In realistic situations, a 6% performance improvement is still attainable. If a large, accurate database exists, near-perfect data association is achieved. Overall, the above technique adjustments provide an improvement of 6.3% (13.6% in realistic, GPS-generated scenarios) in data association accuracy over the initial FAT algorithm and a corresponding 28.8% improvement over the results of the KT itself.by Michael J. O'Brien.S.M

The Feasibility of Quantitatively Characterizing the Vehicle Motion Environment (VME)

https://deepblue.lib.umich.edu/bitstream/2027.42/154108/1/ervin1990.pd

Pattern-theoretic foundations of automatic target recognition in clutter

Issued as final reportAir Force Office of Scientific Research (U.S.

Fusion of Data from Heterogeneous Sensors with Distributed Fields of View and Situation Evaluation for Advanced Driver Assistance Systems

In order to develop a driver assistance system for pedestrian protection, pedestrians in the environment of a truck are detected by radars and a camera and are tracked across distributed fields of view using a Joint Integrated Probabilistic Data Association filter. A robust approach for prediction of the system vehicles trajectory is presented. It serves the computation of a probabilistic collision risk based on reachable sets where different sources of uncertainty are taken into account

Telecommunications and data acquisition systems support for Voyager missions to Jupiter and Saturn, 1972-1981, prelaunch through Saturn encounter

The Deep Space Network has supported the Voyager Project for approximately nine years, during which time implementation, testing, and operational support was provided. Four years of this time involved testing prior to launch; the final five years included network operations support and additional network implementation. Intensive and critical support intervals included launch and four planetary encounters. The telecommunications and data acquisition support for the Voyager Missions to Jupiter and Saturn are summarized