A novel SAR imaging strategy based on compressed sensing

In this paper, we present a novel SAR (synthetic aperture radar) imaging algorithm based on compressed sensing (CS). We first obtain complex SAR images from raw SAR echoes, and then search all targets in complex-image domain by an improved MP (matching pursuit) algorithm. Unlike other CS-based imaging models, our algorithm has several advantages: 1) our algorithm is a two-dimensional (2-D) imaging system, rather than one-dimensional (1-D) imaging models introduced in most existing CS-based imaging algorithms; 2) unlike low efficiencies of most reconstruction algorithms, our method has an efficient reconstruction rate; 3) our imaging model applies existing SAR imaging systems, and inherits current SAR imaging results. The experimental results using real SAR echo data demonstrate the effectiveness of our algorithm.