基于改进最速下降LCMV算法的稳健波束形成

基于线性约束最小方差准则(LCMV)的自适应波束形成技术,在理想条件下能够在期望信号方向保证增益最大,同时在干扰方向形成零陷.但在实际阵列系统中,指向误差、阵元位置误差以及阵元相位误差均使得传统的LCMV准则算法出现性能下降.针对最优权矢量解算问题,提出了基于牛顿法及可变加载约束的改进SD-LCMV算法,并将两者与线性约束LMS算法及递归稳健LCMV算法进行仿真对比,结果验证了改进算法对误差的稳健性.

Robust beam-forming based on improved steepest descent LCMV algorithm

Adaptive beam-forming technology based on linear constrained minimum variance linear constrained minimum variance(LCMV)criterion algorithm can ensure the maximum signal gain in the desired direction and the null formation in undesired direction in ideal condition. In practical array systems,traditional cirterion algorithm based on the LCMV are known to degrade if there exits pointing error,sensor positioning error,and sensor phase error.An improved SD-LCMV algorithm based on Newton method and variable loading constraint is proposed to solve the problem of optimal weight vectors resolving.Simulations of two algorithms are compared with linear constrained LMS algorithm and recursive robust LCMV algorithm. The results verify robustness of the improved algorithm to error.