相干环境下LCMV自适应阵列抗干扰问题研究

相干干扰环境下,自适应阵列性能会急剧下降,常用的处理方法是空间平滑.然而,采用常规均匀空间平滑的自适应阵列对相干干扰的抑制能力较差,而且会损失阵列孔径.该文提出一种改进的相干干扰抑制方案:首先,提出了一种自适应的加权空间平(Weighted Spatial Smoothing,WSS)算法,它将各子阵的相关矩阵进行加权平均,可以最大程度地解相干;然后,在WSS基础上,利用线性约束最小方差(LCMV)准则得到子阵波束形成器最佳权矢量;最后,提出了一种利用子阵间的相位关系对全阵做波束形成的方法.该方案大大提高了阵列对抗相干干扰的能力,同时避免了一般空间平滑后阵列的孔径损失.理论分析和仿真结果说明了方法的有效性和稳健性.

Study on Interference Suppression for LCMV Adaptive Array in Coherent Environment

In environment with coherent interferences, performance of adaptive array will decline dramatically, and the general solution is spatial smoothing. However, adaptive array utilizing conventional Uniform Spatial Smoothing (USS) has poor ability to suppress coherent interferences, and it will lose the aperture of array. In the paper, an improved approach to suppress coherent interferences is proposed. Firstly, the paper presents an adaptive Weighted-Spatial-Smoothing (WSS) algorithm, which, through weighted averaging of the correlation matrices of each sub-array, can de-correlate the coherent interferences effectively. And then, based on WSS, using the Linear-Constrained-Minimum-Variance (LCMV) criterion, the optimal weight vector of sub-array beamformer can be obtained. Finally, considering the phase relationship of each sub-array, an approach for full array beamforming is proposed. The approach highly improvs the array’s ability to suppress the coherent interferences, and avoids the loss of aperture caused by conventional spatial smoothing. Theoretical analysis and computer simulation confirm the availability and robustness of the algorithm.