LAUSR

Video synthetic aperture radar (VideoSAR) provides the potential of high-resolution target images with also high frame rate. Different from the target signal in VideoSAR, target shadow straightforwardly indicates its location and track without suffering from the Doppler shift and smearing induced by the motion modulation. The target shadow can be exploited to realize the real-time tracking of the moving target with VideoSAR. In this letter, we propose a robust single target shadow tracker, which integrates the discriminative correlation filter (DCF) and interacting multiple model probabilistic data association filter (IMM-PDAF) to simultaneously overcome the interference of around clutter and target maneuvers. Considering the dependence between target shadow appearance and its dynamic motion, a filtering template updating strategy based on the estimated mode probability was proposed. The VideoSAR tracking experiment shows that the proposed algorithm outperforms conventional visual tracking techniques in the robustness aspects.