基于云模型的辐射源信号多站分选方法

Multi-Station Sorting Method for Emitter Signal Based on Cloud Model

本文分析了两站和三站时差分选的性能和运行效率,提出了一种基于云模型的辐射源信号多站分选方法.该方法首先利用两站时差分选方法完成脉冲配对与粗分选;然后运用云模型计算各配对成功脉冲集合在时差、脉宽和载频参数维度上的隶属度,合并来自同一辐射源的脉冲集合,实现细分选;最后利用另一个云模型计算配对失败脉冲与细分选后的集合在脉宽、载频和带宽参数维度上的隶属度,归类配对失败脉冲.仿真结果表明,与现有多站时差方法相比,本文通过引入云模型合并时差粗分选结果中来自同一辐射源的脉冲集合,降低了虚警率,同时实现了配对失败脉冲的准确归类,提高了方法的鲁棒性.

In this paper,the performance and operating efficiency of two-station and three-station time difference of arrival(TDOA)sorting are analyzed,and a multi-station sorting method for emitter signal based on cloud model is proposed.Firstly,two-station TDOA sorting method is used to complete the pulse pairing and rough sorting.And then,the sets of puls⁃es from same emitter is merged by using cloud model and calculating membership of each sets in terms of TDOA,pulse width and radio frequency.Finally,another cloud model is used to classified the pulses which failed to pair by calculating the membership of the pulses which failed to pair and the refined sets in pulse width,radio frequency and bandwidth.Simu⁃lation results show that compared with the existing methods,the proposed method can realize the sorting of pulses which failed to pair and reduce the false alarm rate by introducing the cloud model.The robustness of the method is improved.