SAR MOVING TARGET IMAGING USING GROUP SPARSITY

SAR imaging of scenes containing moving targets results in defocusing in the reconstructed images if the SAR observation model used in imaging does not take the motion into account. SAR data from a scene with motion can be viewed as data from a stationary scene, but with phase errors due to motion. Based on this perspective, we formulate the moving target SAR imaging problem as one of joint imaging and phase error compensation. Based on the assumption that only a small percentage of the entire scene contains moving targets, phase errors exhibit a group sparse nature, when the entire data for all the points in the scene are handled together. Considering this structure of motion-related phase errors and that many scenes of interest admit sparse representation in SAR imaging, we solve this joint problem by minimizing a cost function which involves two nonquadratic regularization terms one of which is used to enforce the sparsity of the reflectivity field to be imaged and the other is used to exploit the group sparse nature of the phase errors.