A Subaperture based Approach for SAR Moving Target Imaging by Low-rank and Sparse Decomposition

In this paper, we propose a synthetic aperture radar (SAR) moving-target imaging approach that exploits the low-rank and sparse decomposition (LRSD) of subaperture data. The low-rank component consists of the static background whereas the sparse component captures the moving targets. This allows the reconstruction of a full resolution moving target image separate from the static background image after LRSD. Furthermore, it facilitates the applicability of sparsity-driven moving target imaging in low signal to clutter ratio (SCR) scenarios. We demonstrate the effectiveness of our approach with experiments on synthetic as well as real SAR data.