基于复杂度特征的未知雷达辐射源信号分选

摘要

当前的未知雷达辐射源信号分选方法存在准确率不高和对噪声敏感的问题.该本文应用复杂度特征实现了低信噪比下未知复杂雷达信号的高准确率分选.首先,对接收到的信号进行预处理,然后提取其复杂度特征中的盒维数和稀疏性,并将两者作为分选的特征参数,最后基于KFCM算法实现未知雷达辐射源信号的分选.由仿真结果分析可知,预处理后的信号序列的盒维数和稀疏性分离度高且受噪声的影响小,分选结果令人满意,在信噪比为5 dB时,不同调制类型信号间的分选准确率最低为87%.%Radar emitter sorting rate of current methods is not high and they are sensitive to the Signal Noise Ratio (SNR). In this paper, complexity characteristics are applied to sorting unknown complicated radar signal and a high sorting rate is got. The received signal is pretreatment firstly, then the box dimension and sparseness are extracted and they are used as sorting characteristics. Finally, the sorting is completed by KFCM algorithm. By simulation results, the box dimension and sparseness of pretreatment signal sequence are distinguishable and they are not sensitive to SNR, and the lowest sorting rate of different signal is 87% at SNR=5 dB.