通信辐射源瞬态特征提取和个体识别方法

Extraction of the transient characteristics of the communication radiating source and individual indentification

通信信号的个体识别是近年来非合作通信领域一个重要研究课题.根据瞬态信号的非线性特征,采用递归图的分析方法提取瞬态信号的起始时刻,然后采用小波变换进行特征提取,在此基础上采用遗传算法挑选出分辨能力强的特征,利用支持向量机分类器实现对通信辐射源信号的个体识别.实验结果表明该方法用较少的特征获得较高的正确识别率,正确识别率大于90%.

Individual communication signals identification is an important issue in the field of communication reconnaissance in recent years. The recurrence plot method is proposed to detect the start-up point of the transient signals, which is based on the nonlinear characteristics of the transient signal. Wavelet transform is used to extract features from the transmitters. The most discriminatory features are selected from a large number of wavelet transform features by genetic algorithms, and Support Vector Machines （SVM） are used to realize the individual identification. Experimental results show that the introduced method achieves good accuracy recognition rate in terms of a little features as reference, with the accuracy recognition being more than 90%.