一种处理未知雷达信号的聚类分选方法

针对未知雷达信号的处理,提出了一种新的辐射源聚类分选方法。该方法应用Kohonen网络模型,引入新的权值概念,借鉴熵值分析和统计原理确定权值,计算加权的归一化Minkowsky距离,检验最小距离,根据假设检验合并同类聚类中心,从而实现脉冲的分选。仿真实验结果验证了该方法分选未知雷达信号的有效性。

Clustering approach for deinterleaving unknown radar signals

Aimed at the processing of unknown radar signals,a new clustering approach for deinterleaving the emitters is put forward.By applying Kohonen net model,new conception of weighted value is introduced,weighted values are determined based on entropy and statistical theory,weighted and normalized Minkowsky distance is computed,minimum distance is veried,and similar clustering centers are merged according to hypothesis testing theory.In this way, the interleaved radar signals are sorted into individual cells.Computer simulation results show that the proposed approach can successfully deinterleave unknown radar signals.