小样本雷达辐射源识别的深度学习方法综述

Traditional radar emitter identification methods can no longer meet the needs of identifying new-system radar emitters in the complicate and changeable electromagnetic environment. Deep learning methods can effectively extract the intra-pulse features of the unsorting radar emitter signal,quickly and accurately identify the radar intra-pulse modulation type,model type and emitter individual under complex environments such as low signal-to-noise ratio. However, in the reality, radar emitter signal is difficult to collect and cannot satisfy the training needs of traditional deep learning models. Therefore, the small sample radar emitter identification is one of hotspot and difficult questions of current research. Firstly,this paper reviews the research progress and application of various deep learning methods based on supervised learning for radar emitter recognition with small samples in recent years. Secondly,the research progress of radar emitter identification by small sample learning is introduced. Last,according to the current radar emitter identification research,the challenges and outlook for future research are put forward.