A SPATIOTEMPORAL TWO-STEP PROCESSING METHOD FOR VIDEO SAR MOVING TARGET DETECTION UNDER STRONG CLUTTER AND NOISE CONDITIONS

Video synthetic aperture radar (video SAR) is extensively utilized for dynamic monitoring in complex environments due to its ability to provide continuous imaging. However, its performance is often hindered by strong clutter and noise, leading to challenges such as blurred moving target features and difficulties in detection. This paper introduces a spatiotemporal two-step processing method that reformulates the detection problem as a dual classification problem in both temporal and spatial domains. In the temporal domain, the method employs a multiple-kernel function to suppress noise, while in the spatial domain, it applies a three-term decomposition (TTD) to distinguish moving targets from clutter. Experiments conducted with ICEYE data demonstrate that the proposed method enables efficient and accurate detection of moving targets under strong clutter and noise conditions, providing highly distinguishable results that enhance subsequent applications.