Sparse Imaging-Based Clutter Suppression and Refocusing of MTs in Passive Bistatic SAR

A sparse-imaging-based methodology for the clutter suppression and refocusing of multiple slow-moving targets (MT) in passive bistatic synthetic aperture radar (SAR) is proposed in this paper. The defocused regions of MTs in the bistatic imagery are utilized here. A joint radar projection operator for the static and moving objects is formulated and employed to construct a source separation problem. The Lp norm and square difference maximization constraint are utilized to promote the separation of MT data and the suppression of clutter. After the joint sparse processing, static-scene imagery and MT imagery can be derived simultaneously. Finally, numerical simulations can verify the validity of the proposed methodology.