Title:  Compressed Sensing in Radar with Structured Interference

Committee:

Dr. James McClellan, ECE, Chair , Advisor

Dr. Douglas Williams, ECE

Dr. Mark Davenport, ECE

Dr. Aaron Lanterman, ECE

Dr. Yao Xie, ISyE

Abstract:

Ground clutter has challenged designers of airborne radar since the first examples were 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, that 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.