A Synthetic Framework for Real-World Radar Target Recognition Using HRRP

In recent years, radar automatic target recognition (RATR) using high-resolution range profile (HRRP) has become a research focus. In real-world, HRRPs frequently exhibit open set and long-tailed characteristics, collectively referred to as realistic HRRPrecognition (RHR). The main challenges in such RHR task include: (1) ensuring that tail classes receive sufficient training for feature representation, and (2) mitigating the overconfidence of deep neural network (DNN) model when encountering un