Compressive Sensing Framework for Synthetic Aperture Radar Imaging using OMP Algorithm

Imaging a target or scene is one of the most important applications of Synthetic Aperture Radar (SAR). There are many numbers of algorithms to generate SAR images but, conventional imaging methods sometimes produce higher sidelobe levels in the resultant image which further need to be suppressed to get finer resolutions. In this paper, we proposed a Compressive Sensing (CS) framework based Orthogonal Matching Pursuit (OMP) algorithm for SAR imaging to get highly focused target images and to achieve good resolution in identifying weak scatterers. Initially, the SAR imaging problem is defined as a CS problem and later this problem is solved using Modified-Orthogonal Matching Pursuit (M-OMP) algorithms. From the results, it is observed that the proposed algorithm is showing clearer target images than the conventional imaging methods.