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雷达信号分选识别是现代雷达侦察中必须具备的功能,它在电子对抗和反对抗中起着重要作用。针对复杂电磁环境中雷达辐射源信号识别问题,首要的任务是实现混叠雷达信号的分离,从信号自身特性入手,利用循环谱理论提取雷达信号的循环平稳频率,获得雷达信号在循环平稳维度上的特征,同时构建Givens矩阵,将传统的适用于两路信号的基于三阶循环量的循环平稳度(DCS)盲源分离算法,拓展到可以应用于多路不同循环平稳频率的信号,结合DCS分离准则,并利用该算法实现对雷达信号的分离识别。采用循环统计量能够保留相位信息,且计算量小抗噪声性强,通过公式推导和仿真验证,论证该算法能够实现对于常见的多路雷达信号的有效分选识别。
Radar signal sorting and identification is a necessary function of modern radar reconnaissance, which plays an important role in electronic counter-attack and anti-countermeasure. In order to solve the problem of radar emitter signal identification in complex electromagnetic environment, the primary task is to realize the separation of the aliased radar signal. Starting from the characteristics of the signal, the cyclostationary frequency of the radar signal is extracted by the cyclic spectrum theory. , And builds a Givens matrix. The traditional blind source separation algorithm based on the third-order cyclic magnitude for two-channel signals is extended to a signal that can be applied to a plurality of smoothing frequencies in different cycles. In combination with DCS Separation criteria, and the use of the algorithm to achieve separation of radar signals recognition. By using cyclic statistics, the phase information can be preserved, and the calculation is small and strong anti-noise. Through formula derivation and simulation, it is demonstrated that the algorithm can effectively identify and distinguish common multi-channel radar signals.