Compressed sensing in radar with structured interference
Tuuk, Peter Benjamin
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Ground clutter has challenged designers of airborne radar since it was first developed in the 1940's. Since that time, pulse-Doppler processing and space-time adaptive processing (STAP) have provided significant gains in clutter mitigation. This research examines the mitigation of ground clutter in compressed sensing (CS) radars, which use randomized sampling schemes. The work shows three results: (1) that clutter can be mitigated in these types of systems using the interference covariance matrix, (2) that the interference covariance can be estimated from compressed measurements using low-rank approximation, and (3) that results from random matrix theory can be used to improve processing for both CS radars and in the standard STAP context.