Superresolution Radar Imaging via Peak Search and Compressed Sensing

Compressed sensing (CS)-based imaging technique is considered to be an effective solution for high-resolution radar imaging due to the sparse distribution of the scatterers. Nevertheless, the unoptimized CS-based synthetic aperture radar (SAR) or inverse SAR (ISAR) imaging approach may suffer from the computationally intensive problem when applies it to wideband radar signatures of electrical large-scale targets. In this article, a 2-D superresolution (SR) imaging technique based on peak search and CS (PS-CS) is presented. A PS strategy is first developed to solve the problem of high computational complexity of CS-based method in scattering parameter estimation. SR imaging result is then achieved by extrapolating the estimated parameters of scattering along with the observing angle dimension and frequency dimension. The numerical and measurement data acquired from different man-made targets are presented to demonstrate the feasibility and usefulness of the proposed technique for SR radar imaging.