基于协方差矩阵重构的稳健自适应波束形成算法

Robust Adaptive Beamforming Algorithm Based on Covariance Matrix Reconstruction

针对大角度失配和采样协方差矩阵中包含有期望信号时,传统自适应波束形成器性能极剧下降的问题,提出了基于协方差矩阵重构的稳健自适应波束形成算法。该算法将全空域划分成若干互不重叠的区域,分别对应干扰区域和期望信号区域,先利用标准Capon波束形成器及采样协方差矩阵的最小特征值对干扰加噪声协方差矩阵进行重构,再利用MUSIC谱估计法重构出信号协方差矩阵,以其主特征向量估计出期望信号导引向量,最终得到自适应波束形成器的最优权值。仿真实验结果表明,在少快拍和大角度失配情况下算法具有良好的性能。

In view of the large angle mismatch and sample covariance matrix containing the desired signal,the traditional adaptive beamformer performance is degraded sharply,this paper proposed a robust adaptive beamforming algorithm based on covariance reconstruction.The algorithm divided the whole airspace into several non-overlapping regions,respectively corresponding to the interference region and desired signal region.Firstly,the standard Capon beamformer and the smallest eigenvalue of sample covariance matrix were used to reconstruct the interference and noise covariance matrix.Secondly,the MUSIC spectrum estimation method was used to reconstruct the signal covariance matrix,and the main eigenvector of signal covariance matrix was used to estimate desired signal steering vector,thus the optimum weight vector of adaptive beamformer was obtained.Simulation result showed that algorithm had good performance in the case of few snapshots and large angle mismatch.