Sparsity Based Ground Moving Target Imaging via Multi-Channel SAR

State-of-the-art Ground Moving Target Indicator (GMTI) schemes include the Displaced Phase Center Antenna (DPCA) and Along Track Interferometry (ATI) which are commonly used image-based dual- channel techniques for moving target detection. In the present paper, we provide a different perspective for solving GMTI tasks by generalising the ground moving targets imaging as a parameter estimation and an optimisation problem. A sparsity based ground target imaging approach is described to improve the image quality for moving targets and estimate their states. By exploiting the fact that moving targets are highly sparse in the observed scene and feasible velocity space, the proposed method constructs a velocity map for the illuminated region, and combines this map with a sparsity based optimisation algorithm to realise the image formation. The performance of the presented method is demonstrated through GOTCHA airborne SAR data set.