基于Pearson相关性的雷达交叠信号识别

针对复杂电磁环境下多部雷达同时到达信号频域交叠时难以分选识别的问题,分析了信号交叠对于雷达信号识别模块性能的影响；在此基础上面向识别需求,基于Pearson算法研究了交叠信号分选的处理方法。从信息论视角来说,两个信号脉冲波形相关性越弱,则其所表达的信息量越大,特征相关度越低。在信号脉冲数一定时,基于Pearson算法可以选择相关性较弱的信号脉冲载波,以削弱同时信号交叠的影响。通过实验,发现利用选择后的弱相关信号脉冲载波特征来表达信号特性,能有效降低数据维度,尽可能减少信息丢失,有利于达到鲁棒的识别效果,因此该方法可为同时到达信号交叠下的信号识别提供有效途径参考。

Radar Overlapping Signal Recognition Method Based on Pearson Correlation

It is difficult to sort and identify the overlapping signals of multiple radars arriving at the same time in the complex electromagnetic environment. Aiming at this problem, the influence of signal overlapping on the performance of radar signal recognition module is analyzed. On this basis, the processing method of overlapping signal sorting is studied based on Pearson algorithm. From the perspective of information theory, the weaker the correlation of two signal pulse waveforms is, the more information they express and the lower the correlation of features is. When the number of signal pulses is fixed, the carrier of signal pulses with weak correlation can be selected based on Pearson algorithm to reduce the impact of simultaneous signal overlapping. Through the experiments, it is found that using the selected weak correlation signal pulse carrier characteristics to express the signal characteristics can effectively reduce the data dimension and minimize information loss as much as possible, conducive to robust recognition. Therefore, this method can provide an effective reference for signal recognition under simultaneous arrival signal overlapping.