Adaptive waveforms for automatic target recognition and range-doppler ambiguity mitigation in cognitive sensor.

摘要

This dissertation shows the performance of adaptive waveforms when applied to two radar applications. One application is automatic target recognition (ATR) and the other application is range-Doppler ambiguity mitigation. The adaptive waveforms are implemented via a feedback loop from receiver to transmitter, such that previous radar measurements affect how the adaptive waveforms proceed. For the ATR application, adaptive transmitter can change the waveform's temporal structure to improve target recognition performance. For range-Doppler ambiguity mitigation application, adaptive transmitter can change the pulse repetition frequency (PRF) to mitigate range and Doppler ambiguity. In the ATR application, commercial electromagnetic software is used to create high-fidelity aircraft target signatures. Realistic waveform constraints are applied to show radar performance. The radar equation is incorporated into the waveform design technique and template-based classification is performed. Translation invariant feature is used for inaccurately known range scenario. The performance of adaptive waveforms is evaluated with not only a monostatic radar, but also widely separated MIMO radar. In MIMO radar, multiple transmit waveforms are used, but spectral leakage caused by constant-modulus constraint shows minimal interference effect. In the range-Doppler ambiguity mitigation application, particle-filter-based track-before-detect for a single target is extended to track and detect multiple low signal-to-noise ratio (SNR) targets, simultaneously. To mitigate ambiguity, multiple PRFs are used and improved PRF selection technique is implemented via predicted entropy computation when both blind and clutter zones are considered.