  The existing Video Synthetic Aperture Radar (ViSAR) moving target shadow
detection methods based on deep neural networks mostly generate numerous false
alarms and missing detections, because of the foreground-background
indistinguishability. To solve this problem, we propose a method to suppress
complicated background of ViSAR for moving target detection. In this work, the
proposed method is used to suppress background; then, we use several target
detection networks to detect the moving target shadows. The experimental result
shows that the proposed method can effectively suppress the interference of
complicated back-ground information and improve the accuracy of moving target
shadow detection in ViSAR. The existing Video Synthetic Aperture Radar (ViSAR)
moving target shadow detection methods based on deep neural networks mostly
generate numerous false alarms and missing detections, because of the
foreground-background indistinguishability. To solve this problem, we propose a
method to suppress complicated background of ViSAR for moving target detection.
In this work, the proposed method is used to suppress background; then, we use
several target detection networks to detect the moving target shadows. The
experimental result shows that the proposed method can effectively suppress the
interference of complicated back-ground information and improve the accuracy of
moving target shadow detection in ViSAR.
