Radar emitter signal sorting is one of the key technologies of radar signal reconnaissance and an important part of battlefield situation awareness. This paper systematically sorts out the mainstream technologies of radar emitter signal sorting, and explains the main research directions and progress of radar emitter signal sorting from three perspectives: radar emitter signal sorting based on inter-pulse modulation features, intra-pulse modulation features, and machine learning. It also focuses on explaining the principles and characteristics of the latest sorting technologies such as deep neural networks and data stream clustering. Finally, the shortcomings of existing radar emitter signal sorting technologies are summarized and future trends are predicted.
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