High resolution SAR target reconstruction from compressive measurements with prior knowledge

In this paper, an effective prior knowledge based framework for target reconstruction from compressive measurements is proposed. In this framework, a traditional compressed imaging method is firstly introduced which indicates that for a range cell containing K strongest scattering points can be reconstructed based on the theory of compressive sensing. Secondly, a greedy iteration algorithm is modified which utilizes some prior knowledge of the target during the reconstruction step. The experiments are carried on the Moving and Stationary Target Acquisition and Recognition (MSTAR) database and the results show the effectiveness of our framework for target reconstruction.