基于最大信噪比的盲源分离雷达抗主瓣干扰方法

A Radar Mainlobe Jamming Suppression Method of BSS Based on Maximum Signal Noise Ratio

针对现有压制干扰从主瓣进入雷达天线,传统副瓣抗干扰方法失效的问题。提出一种应用最大信噪比准则的盲源分离抗主瓣干扰方法。首先提出了盲源分离应用于雷达抗主瓣干扰的模型,估计信号源个数后构建基于信噪比的目标函数,而后选择求解得到的广义特征向量构造分离矩阵。与传统算法相比,该方法不需要进行迭代运算,有效降低了计算复杂度。经过仿真分析,验证该方法能够有效分离混合信号,具有较高的分离效率。

A method of BSS algorithm is proposed on the character that Signal Noise Ratio(SNR)is maximal. This method is aimed to solve the problem when the suppress jamming pour into the mainlobe of radar antenna which would severely degenerate the performance of radar as the common ECCM measures of sidelobe have no effect. At first,the signal model of mainlobe jamming suppression based on BSS is given. Then the objective function of SNR is presented after the signal source number is estimated. The unmixing matrix is composed by the chose generalized eigenvectors to achieve the separation effect. Compared to the typical method,this one don’t need any iterative operation with low computational complexity. Computer simulation demonstrates that this method can separate the mixture signal with obviously responsive time superiority.