期望信号稳健阻塞的协方差矩阵重构波束形成算法

针对期望信号导向矢量存在失配时自适应波束形成器性能下降的问题,提出期望信号稳健阻塞的干扰噪声协方差矩阵重构算法。首先,构造角度展宽的信号阻塞矩阵,完成回波数据中期望信号的分离,进而利用无污染的回波数据计算准干扰噪声协方差矩阵。接着,对准干扰噪声协方差矩阵做特征分解,借助矩阵投影变换完成干扰噪声协方差矩阵的准确重构。最后,对剔除掉干扰和噪声分量的采样协方差矩阵做特征分解,完成期望信号导向矢量的有效估计。理论分析和仿真结果表明,所提算法不仅具有近乎理想的性能,还具有较低的计算复杂度。

Covariance matrix reconstruction algorithm via desired signal robustly blocking for beamforming

Focusing on the performance reduction problem of the adaptive beamformer when the desired signal (DS) steering vector mismatch exists, an interference-plus-noise covariance matrix (INCM) reconstruction method via DS robustly blocking is proposed. First of all, the signal blocking matrix with angle broadening is constructed to separate the DS from the echo data, thus the quasi INCM is calculated with the uncontaminated echo data. Then after applying Eigen-decomposition on the quasi INCM, the INCM is accurately reconstructed by means of matrix projection transition. Finally, the effective estimation of the DS steering vector is completed by the way of eigen-decomposing the sample covariance matrix, of which the interference-plus-noise component has been eliminated. Theory analysis and simulation result show that the proposed algorithm has not only almost ideal performance but also low complexity.