Compressive sensing SAR imaging with real data

Abstract

As an active and coherent microwave high resolution imaging system, Synthetic Aperture Radar (SAR) has the capability to image in all weather and day-or-night conditions. Recent advent of theory of Compressive Sensing (CS) has introduced a novel concept that an unknown sparse signal can be recovered exactly with an overwhelming probability even with highly sub-Nyquist-rate samples. In this paper, a new scheme for the test bed of CS based SAR imaging is proposed. Experimental results on some real raw SAR data reveal that there are some practical limitations on the use of CS based SAR imaging, especially for complex imaging scenes and the systems with low Signal-to-Noise Ratio (SNR).