基于ICA的交叉极化干扰抑制算法

Cross⁃Polarization Interference Suppression Algorithm Based on Independent Component Analysis

针对极化复用模式中引入的交叉极化干扰问题,利用一种基于独立成分分析(ICA)的盲分离算法,无需信号先验知识和后续解调即可从观测信号中分离出源信号,达到消除极化干扰的目的。该算法基于线性瞬时混合模型,对峭度对比函数进行精确线性搜索优化,选取最佳步长,解决了盲分离信号中的排序问题。文中对不同信噪比和极化隔离度下的分离效果进行了仿真,仿真结果表明,该算法具有较好的分离性能,且在强交叉极化干扰和低信噪比下的性能较为稳定。

Aiming at the problem of cross⁃polarization interference introduced in polarization multiplexing mode,a blind separation algorithm based on independent component analysis(ICA)is used to separate the source signal from the observed signal without prior signal knowledge and subsequent demodulation,so as to eliminate the polarization in⁃terference.Based on the linear instantaneous mixture model,the algorithm performs exact line search optimization on the kurtosis contrast function,selects the best step size,and solves the sorting problem in blind source separation.We simulate the separation effect under different signal⁃to⁃noise ratios(SNR)and polarization isolation degrees.The simu⁃lation results show that the algorithm has good separation performance and the performance is relatively stable under strong cross⁃polarization interference and low signal⁃to⁃noise ratio.