SAR SHIP DETECTION IN RANGE-COMPRESSED DOMAIN BASED ON LSTM METHOD

Most of the conventional ship detection methods based on synthetic aperture radar (SAR) intends to process the focused images, which does not take full advantages of the intermediate data in the SAR imaging process. In this paper, we introduce a new framework that treats a two-dimensional point target as multiple one-dimensional sequences in the range-compressed domain, and then employs a Long Short-Term Memory (LSTM)-based network to perform the ship detection, thus reducing the computational burden and improving efficiency significantly. To validate the effectiveness of our proposed method, we conduct experiments on real SAR data. The results demonstrate the superiority of our framework in ship detection tasks.