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Micro-Doppler is defined as scattering produced by non-rigid-body motion. This dissertation involves the design of a multiple frequency continuous wave (MFCW) radar for micro-Doppler research and detection and classification algorithm design. First, sensor hardware is developed and tested. Various design tradeoffs are considered, with the application of micro-Doppler based detection and classification in mind. A diverse database of MFCW radar micro-Doppler signatures was collected for this dissertation. The micro-Doppler signature database includes experimental data from human, vehicle, and animal targets. Signatures are acquired from targets with varying ranges, velocities, approach angles, and postures. The database is analyzed for micro-Doppler content with a focus on its application to target classification. Joint time-frequency detection algorithms are developed to improve detection performance by exploiting noise-spreading and the micro-Doppler phenomenon. Following detection algorithm development, this dissertation covers the design of micro- Doppler feature extraction, feature selection, and classification algorithms. Feature selection is performed automatically via a Fisher score initialized sequential backward selection algorithm. Classification is performed using two distinct approaches: a generative statistical classification algorithm based on Gaussian mixture models (GMMs) and a discriminative statistical classification algorithm based on support vector machines (SVMs). Classifier performance is analyzed in detail on a micro-Doppler signature database acquired over a three-year period. Both the SVM and GMM classifiers perform well on the radar target classification task (high accuracy, low nuisance alarm probability, high F-measure, etc.). The performance of both classifiers is remarkably similar, and neither algorithm dominates the other in any performance metric when using the chosen feature set. (However, the difference between SVM and GMM classification accuracy becomes statistically significant when many redundant features are present in the feature set.) The accuracy of both classifiers is shown to vary as a function of approach angle, which physically corresponds to the angular dependence of micro-Doppler. The results suggest that overall classifier performance is more sensitive to feature selection than classifier selection (with GMM being more sensitive to redundant features than SVM). Both classifiers are robust enough to handle human targets attempting to evade detection by either army crawling or hands-and-knees crawling. / text

Radar altimeter experiments have shown the need for expanding the downward-looking, single-beam system into a multiple beam radar altimeter employing off-nadir altimetry so that information from a wider swath can be obtained from a single overflight. Problems associated with off-nadir altimetry include the effects of pointing angle errors on the return information and difficulty in performing accurate range tracking. In order to understand these problems, investigation of the sensitivity of the average return waveforms to pointing errors is necessary. These waveforms are computed using a convolutional model, including the effects of asymmetric antenna patterns, which is representative of NASA’s Multimode Airborne Radar Altimeter. The necessary convolutions are most efficiently performed by a method that uses the fast Fourier transform. The modeled waveforms are then used to devise a method that provides an estimate the pointing angle. / Master of Science

Approved for public release, distribution is unlimited / Presently, the required data file to be loaded onto the Radar Warning Receiver (RWR) onboard the F-16 aircraft is done manually by the aircraft technicians, two to three hours prior to the actual flight time. This process should be automated. As such there is a need to look into the use of wireless transmission technology to complement or replace the manual method of loading the critical data file from the command station onto every F-16 aircraft. The present wireless technology is relatively mature and stable. In this thesis, the feasibility of incorporating and adapting this technology for use in the flight line environment is examined. The propagation effect in wireless transmission is also studied and recommendations proposed with regards to the installation of wireless facilities in the flight line. In addition, the EDNA, a portable maintenance aid that comes with the F-16 aircraft for loading the data file, has to be upgraded. Hence, a system feasibility study is carried out to adapt or upgrade the present equipment to wireless transmission capability. / Major, Republic of Singapore Air Force