Application of Deep Learning Approaches in SAR ATR

Abstract

In the field of Synthetic Aperture Radar (SAR) image interpretation, the Automatic Target Recognition (ATR) has always been the focus and hotspot in this field, which is also the research difficulty in this field. The SAR ATR is generally composed of three steps: extraction of Region of Interest (RoI), target identification, and target classification. The complex flow not only limits the efficiency of SAR ATR, but also makes the overall optimization of the model difficult to be carried out, which restricts the accuracy. This paper discusses Faster R-CNN and SSD adopted from the computer vision and shows how those approaches enable significantly improved performance for SAR ATR. The validity of the deep learning method in the field of automatic target recognition for SAR images and the nature of the university are verified, which lays the foundation for further research.