Radar imaging from a spinning spacecraft

The feasibility of imaging the surface of Venus using a synthetic aperture radar in a spin stabilized Pioneer class spacecraft operating in an eccentric orbit is studied. Imaging radar fundamentals, constraints, power requirements and data processing considerations are reviewed. Additional effects due to operation from an elliptical orbit with a spinning spacecraft are covered. Recommended spin parameters are determined by simulations. Extensions to include noncoherent integration and stereo coverage are briefly reviewed. The results indicate that resolution on the order of 100 meters can be obtained from a 0.2 eccentricity orbit using a 2 meter antenna and reasonable transmitter power levels

Micro-Doppler Extraction and ANalysis of the Ballistic Missile Using RDA Based on the Flight Scenario

11Yscopu

OPTIC: Orbiting Plutonian Topographic Image Craft Proposal for an Unmanned Mission to Pluto

The proposal for an unmanned probe to Pluto is presented and described. The Orbiting Plutonian Topographic Image Craft's (OPTIC's) trip will take twenty years and after its arrival, will begin its data collection which includes image and radar mapping, surface spectral analysis, and magnetospheric studies. This probe's design was developed based on the request for proposal of an unmanned probe to Pluto requirements. The distinct problems which an orbiter causes for each subsystem of the craft are discussed. The final design revolved around two important factors: (1) the ability to collect and return the maximum quantity of information on the Plutonian system; and (2) the weight limitations which the choice of an orbiting craft implied. The velocity requirements of this type of mission severely limited the weight available for mission execution-owing to the large portion of overall weight required as fuel to fly the craft with present technology. The topics covered include: (1) scientific instrumentation; (2) mission management; (3) power and propulsion; (4) attitude and articulation control; (5) structural subsystems; and (6) command, control, and communication

Next Generation Very Large Array Memo No. 6, Science Working Group 1: The Cradle of Life

This paper discusses compelling science cases for a future long-baseline interferometer operating at millimeter and centimeter wavelengths, like the proposed Next Generation Vary Large Array (ngVLA). We report on the activities of the Cradle of Life science working group, which focused on the formation of low- and high-mass stars, the formation of planets and evolution of protoplanetary disks, the physical and compositional study of Solar System bodies, and the possible detection of radio signals from extraterrestrial civilizations. We propose 19 scientific projects based on the current specification of the ngVLA. Five of them are highlighted as possible Key Science Projects: (1) Resolving the density structure and dynamics of the youngest HII regions and high-mass protostellar jets, (2) Unveiling binary/multiple protostars at higher resolution, (3) Mapping planet formation regions in nearby disks on scales down to 1 AU, (4) Studying the formation of complex molecules, and (5) Deep atmospheric mapping of giant planets in the Solar System. For each of these projects, we discuss the scientific importance and feasibility. The results presented here should be considered as the beginning of a more in-depth analysis of the science enabled by such a facility, and are by no means complete or exhaustive.Comment: 51 pages, 12 figures, 1 table. For more information visit https://science.nrao.edu/futures/ngvl

Advanced signal processing tools for ballistic missile defence and space situational awareness

The research presented in this Thesis deals with signal processing algorithms for the classification of sensitive targets for defence applications and with novel solutions for the detection of space objects. These novel tools include classification algorithms for Ballistic Targets (BTs) from both micro-Doppler (mD) and High Resolution Range Profiles (HRRPs) of a target, and a space-borne Passive Bistatic Radar (PBR) designed for exploiting the advantages guaranteed by the Forward Scattering (FS) configuration for the detection and identification of targets orbiting around the Earth.;Nowadays the challenge of the identification of Ballistic Missile (BM) warheads in a cloud of decoys and debris is essential in order to optimize the use of ammunition resources. In this Thesis, two different and efficient robust frameworks are presented. Both the frameworks exploit in different fashions the effect in the radar return of micro-motions exhibited by the target during its flight.;The first algorithm analyses the radar echo from the target in the time-frequency domain, with the aim to extract the mD information. Specifically, the Cadence Velocity Diagram (CVD) from the received signal is evaluated as mD profile of the target, where the mD components composing the radar echo and their repetition rates are shown.;Different feature extraction approaches are proposed based on the estimation of statistical indices from the 1-Dimensional (1D) Averaged CVD (ACVD), on the evaluation of pseudo-Zerike (pZ) and Krawtchouk (Kr) image moments and on the use of 2-Dimensional (2D) Gabor filter, considering the CVD as 2D image. The reliability of the proposed feature extraction approaches is tested on both simulated and real data, demonstrating the adaptivity of the framework to different radar scenarios and to different amount of available resources.;The real data are realized in laboratory, conducting an experiment for simulating the mD signature of a BT by using scaled replicas of the targets, a robotic manipulator for the micro-motions simulation and a Continuous Waveform (CW) radar for the radar measurements.;The second algorithm is based on the computation of the Inverse Radon Transform (IRT) of the target signature, represented by a HRRP frame acquired within an entire period of the main rotating motion of the target, which are precession for warheads and tumbling for decoys. Following, pZ moments of the resulting transformation are evaluated as final feature vector for the classifier. The features guarantee robustness against the target dimensions and the initial phase and the angular velocity of its motion.;The classification results on simulated data are shown for different polarization of the ElectroMagnetic (EM) radar waveform and for various operational conditions, confirming the the validity of the algorithm.The knowledge of space debris population is of fundamental importance for the safety of both the existing and new space missions. In this Thesis, a low budget solution to detect and possibly track space debris and satellites in Low Earth Orbit (LEO) is proposed.;The concept consists in a space-borne PBR installed on a CubeSaT flying at low altitude and detecting the occultations of radio signals coming from existing satellites flying at higher altitudes. The feasibility of such a PBR system is conducted, with key performance such as metrics the minimumsize of detectable objects, taking into account visibility and frequency constraints on existing radio sources, the receiver size and the compatibility with current CubeSaT's technology.;Different illuminator types and receiver altitudes are considered under the assumption that all illuminators and receivers are on circular orbits. Finally, the designed system can represent a possible solution to the the demand for Ballistic Missile Defence (BMD) systems able to provide early warning and classification and its potential has been assessed also for this purpose.The research presented in this Thesis deals with signal processing algorithms for the classification of sensitive targets for defence applications and with novel solutions for the detection of space objects. These novel tools include classification algorithms for Ballistic Targets (BTs) from both micro-Doppler (mD) and High Resolution Range Profiles (HRRPs) of a target, and a space-borne Passive Bistatic Radar (PBR) designed for exploiting the advantages guaranteed by the Forward Scattering (FS) configuration for the detection and identification of targets orbiting around the Earth.;Nowadays the challenge of the identification of Ballistic Missile (BM) warheads in a cloud of decoys and debris is essential in order to optimize the use of ammunition resources. In this Thesis, two different and efficient robust frameworks are presented. Both the frameworks exploit in different fashions the effect in the radar return of micro-motions exhibited by the target during its flight.;The first algorithm analyses the radar echo from the target in the time-frequency domain, with the aim to extract the mD information. Specifically, the Cadence Velocity Diagram (CVD) from the received signal is evaluated as mD profile of the target, where the mD components composing the radar echo and their repetition rates are shown.;Different feature extraction approaches are proposed based on the estimation of statistical indices from the 1-Dimensional (1D) Averaged CVD (ACVD), on the evaluation of pseudo-Zerike (pZ) and Krawtchouk (Kr) image moments and on the use of 2-Dimensional (2D) Gabor filter, considering the CVD as 2D image. The reliability of the proposed feature extraction approaches is tested on both simulated and real data, demonstrating the adaptivity of the framework to different radar scenarios and to different amount of available resources.;The real data are realized in laboratory, conducting an experiment for simulating the mD signature of a BT by using scaled replicas of the targets, a robotic manipulator for the micro-motions simulation and a Continuous Waveform (CW) radar for the radar measurements.;The second algorithm is based on the computation of the Inverse Radon Transform (IRT) of the target signature, represented by a HRRP frame acquired within an entire period of the main rotating motion of the target, which are precession for warheads and tumbling for decoys. Following, pZ moments of the resulting transformation are evaluated as final feature vector for the classifier. The features guarantee robustness against the target dimensions and the initial phase and the angular velocity of its motion.;The classification results on simulated data are shown for different polarization of the ElectroMagnetic (EM) radar waveform and for various operational conditions, confirming the the validity of the algorithm.The knowledge of space debris population is of fundamental importance for the safety of both the existing and new space missions. In this Thesis, a low budget solution to detect and possibly track space debris and satellites in Low Earth Orbit (LEO) is proposed.;The concept consists in a space-borne PBR installed on a CubeSaT flying at low altitude and detecting the occultations of radio signals coming from existing satellites flying at higher altitudes. The feasibility of such a PBR system is conducted, with key performance such as metrics the minimumsize of detectable objects, taking into account visibility and frequency constraints on existing radio sources, the receiver size and the compatibility with current CubeSaT's technology.;Different illuminator types and receiver altitudes are considered under the assumption that all illuminators and receivers are on circular orbits. Finally, the designed system can represent a possible solution to the the demand for Ballistic Missile Defence (BMD) systems able to provide early warning and classification and its potential has been assessed also for this purpose

SISAR imaging for space debris based on nanosatellites

The increasing amount of space debris poses a growing challenge in the development of space travel. In previous work, a proposed system comprising of a low budget space-borne passive radar based on CubeSAT, flying in Low Earth Orbit (LEO), demonstrated promising results in terms of space debris detection performance. In this work, a novel shadow inverse synthetic aperture radar (SISAR) model for space debris imaging based on nanosatellite is presented. An analysis of the received forward scattering signal is provided along with a novel model for moving transmitters and receivers SISAR imaging. Using simulated data and assuming different scenarios, the performance of the new algorithm is assessed; wherein, a classification scheme is applied using the output of the SISAR algorithm for classification between simple target shapes

A Millimeter-Wave Radar Microfabrication Technique and Its Application in Detection of Concealed Objects.

Millimeter-wave (MMW) radars are envisioned for a number of safety and security applications such as collision-avoidance, navigation and standoff target detection in all weather conditions. This work focuses on two MMW radar applications: (1) phenomenology of radar backscatter from the human body for the purpose of identification and detection of concealed objects on the body (2) microfabrication of advanced MMW radar to achieve compact and low-cost systems for autonomous navigation. In MMW band, the wavelength (1 mm ~ 1 cm) is long enough to allow signal penetration through cluttered atmosphere and clothing with little attenuation and short enough to allow for fabrication of small-size radar systems. Hence, this frequency band is well suited for the design of small sensors capable of obstacle detection and navigation in heavily cluttered environment and detecting hidden objects carried by individuals. For this purpose, a novel non-imaging approach is developed for distinction of walking human body and concealed carried object using polarimetric backscatter Doppler spectrum. This approach does not need radiometric calibration of the radar and preparation of the subject for radar interrogation. It is shown that a coherent polarimetric radar at W-band (95 GHz) or higher frequencies can be used for standoff detection of concealed carried objects. Motivated by these results, the thesis also includes an investigation on developing a technology for compact MMW radar systems. A micromachined, high-resolution, compact and low-power imaging MMW radar operating at 240 GHz intended for obstacle detection in complex environment is introduced. A frequency scanning antenna array micromachined from three layers of stacked silicon wafers is designed to provide 20 beamwidth in azimuth and 80 in elevation with azimuthal beam scanning range of ± 250. The frequency beam scanning is enabled by a meander rectangular waveguide with a slot array on its broad wall to feed linear microstrip patch antennas microfabricated on a suspended Parylene membrane. This technique offers high fabrication precision; provide easy fabrication and integration with active devices. The performances of the passive components of the radar system are verified using a WR-3 S-parameter and a near-field measurement systems.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91484/1/mvahid_1.pd

Application of advanced technology to space automation

Automated operations in space provide the key to optimized mission design and data acquisition at minimum cost for the future. The results of this study strongly accentuate this statement and should provide further incentive for immediate development of specific automtion technology as defined herein. Essential automation technology requirements were identified for future programs. The study was undertaken to address the future role of automation in the space program, the potential benefits to be derived, and the technology efforts that should be directed toward obtaining these benefits

Long-Range Imaging Radar for Autonomous Navigation

This thesis describes the theoretical and practical implementation of a long-range high-resolution millimetre wave imaging radar system to aid with the navigation and guidance of both airborne and ground-based autonomous vehicles. To achieve true autonomy, a vehicle must be able to sense its environment, comprehensively, over a broad range of scales. Objects in the immediate vicinity of the vehicle must be classified at high resolution to ensure that the vehicle can traverse the terrain. At slightly longer ranges, individual features such as trees and low branches must be resolved to allow for short-range path planning. At long range, general terrain characteristics must be known so that the vehicle can plan around difficult or impassable obstructions. Finally, at the largest scale, the vehicle must be aware of the direction to its objective. In the past, short-range sensors based on radar and laser technology have been capable of producing high-resolution maps in the immediate vicinity of the vehicle extending out to a few hundred metres at most. For path planning, and navigation applications where a vehicle must traverse many kilometres of unstructured terrain, a sensor capable of imaging out to at least 3km is required to permit mid and long-range motion planning. This thesis addresses this need by describing the development a high-resolution interrupted frequency modulated continuous wave (FMICW) radar operating at 94GHz. The contributions of this thesis include a comprehensive analysis of both FMCW and FMICW processes leading to an effective implementation of a radar prototype which is capable of producing high-resolution reflectivity images of the ground at low grazing angles. A number of techniques are described that use these images and some a priori knowledge of the area, for both feature and image based navigation. It is shown that sub-pixel registration accuracies can be achieved to achieve navigation accuracies from a single image that are superior to those available from GPS. For a ground vehicle to traverse unknown terrain effectively, it must select an appropriate path from as long a range as possible. This thesis describes a technique to use the reflectivity maps generated by the radar to plan a path up to 3km long over rough terrain. It makes the assumption that any change in the reflectivity characteristics of the terrain being traversed should be avoided if possible, and so, uses a modified form of the gradient-descent algorithm to plan a path to achieve this. The millimetre wave radar described here will improve the performance of autonomous vehicles by extending the range of their high-resolution sensing capability by an order of magnitude to 3km. This will in turn enable significantly enhanced capability and wider future application for these systems