TARGET DETECTION FROM MICROWAVE IMAGING BASED ON RANDOM SPARSE ARRAY AND COMPRESSED SENSING

This paper proposes an imaging scheme using a random sparse array (RSA) structure for radar target detection using compressed sensing (CS). The array collects sparse measurements with less collection time and data storage. Two schemes of the RSA are considered, random SAR mode and random array mode. Performances of both static and moving target detections are investigated. Performance of RSA with CS is compared with that using full SAR data with conventional back-projection (BP) method for static target detection and full uniform linear array (ULA) data with conventional beamforming (CBF) method for moving target detection. Simulation and real experimental tests are provided to verify the proposed target imaging scheme. Results show that RSA imaging with CS can perform better than normal SAR and ULA with conventional imaging methods. However, when environment is complicated and background too noisy, CS may have degraded performance.