基于协方差矩阵优化重构的稳健波束形成算法

A robust beamforming algorithm based on optimal reconstruction of covariance matrix

针对一般自适应波束形成器在模型失配误差存在时性能下降严重的问题,提出一种基于干扰加噪声协方差矩阵优化重构的稳健波束形成算法。该算法通过稀疏重构的方法剔除样本协方差矩阵中的期望信号分量;利用子空间扩展知识建立导向矢量不确定集约束,优化干扰加噪声协方差矩阵;基于最大化阵列输出功率准则建立导向矢量误差优化模型,通过循环迭代的方法得出最优加权矢量;理论分析及仿真实验结果表明:该算法在目标来波方向误差和阵元位置误差存在时具有稳健性。

Focusing on the problem that serious performance degradation of general adaptive beamformers in the presence of model mismatch error,a robust beamforming algorithm based on optimal reconstruction of interference plus noise covariance matrix is proposed in this paper.Firstly,the expected signal components in the sample covariance matrix are eliminated by sparse reconstruction method to estimate the interference plus noise covariance matrix.Then,based on the knowledge of subspace expansion,the interference plus noise covariance matrix is optimized by establishing steering vector uncertainty set constraints.After that,a convex optimization model of target steering vector is established in order to maximize array output power and correct the target steering vector.Finally,the model is solved by cyclic iteration method and the optimal weight is obtained.Theoretical analysis and simulation results demonstrate the robustness of the proposed algorithm under target arrival direction error and array position error.