威胁雷达信号的分选识别是雷达对抗侦察系统的重要任务，是影响对抗成败的因素之一。针对雷达数量大幅增加、信号调制样式多样、信号密度越来越高的复杂电磁环境，提出了一种TOA折叠聚类的威胁雷达信号识别方法。该方法首先对截获的脉冲流进行TOA折叠分选，然后用DBSCAN聚类算法提取数据，最后进行威胁雷达信号模板匹配识别。仿真结果表明，该方法在复杂环境下能够分选出目标雷达信号，对复杂体制的雷达信号适应能力强。

The identification of the threat radar signal is an important task of the radar reconnaissance system, and is one of the factors that affect the success or failure of the countermeasure. Considering the complex electromagnetic environment with the increasing number of radars, the diversity of signal modulation modes and the increasing signal density, we proposed a new method for threat radar signal recognition based on TOA folding clustering. The method firstly performs TOA folding and sorting of the intercepted pulse stream, then extracts the data with DBSCAN clustering algorithm, and finally performs the template matching recognition of the threat radar signal. The simulation results show that the method can sort out the target radar signal in complex environment, and can adapt to the complex modulation of radar signal.