利用空间平滑的协方差秩最小化DOA估计方法

针对传统波达方向角估计算法在相干信号及非均匀噪声下估计精度差、分辨率低的问题，基于空间平滑方法，提出一种接收信号协方差矩阵秩最小化波达方向估计方法．在传统空间平滑方法的基础上，所提算法将接收信号协方差矩阵分别左右乘交换矩阵以得到空间后向平滑协方差矩阵；而后基于平滑矩阵的低秩性，将协方差矩阵重构为无噪声协方差矩阵；最后利用传统MUSIC算法实现波达方向估计．仿真结果表明，与传统MUSIC算法、基于矩阵补全理论的MUSIC算法和秩迹最小化算法相比，所提算法能较好地抑制非均匀噪声影响，且在相干条件下具有较好的波达方向估计性能．

Method for estimation of covariance rank minimization DOA by exploiting spatial smoothing

Focusing on the problem of poor accuracy and low resolution acquired by the traditional direction of arrival (DOA) estimation algorithm in the cases of the coherent signals and non-uniform noise and based on the spatial smoothing method, a DOA estimation approach via minimizing the rank of the covariance matrix of the received signal is developed. Following the traditional spatial smoothing approach, the covariance matrix of the received signal is multiplied by a certain switch matrix on the left and right sides in the proposed method, respectively, and then the spatial backward smoothing covariance matrix can be obtained. In what follows, the covariance matrix can be reconstructed into a noise-free one by exploiting the low rank property of the smoothing matrix. Finally, the DOA can be implemented by the traditional MUSIC algorithm. Simulation results demonstrate that, compared to the traditional MUSIC, matrix completion based MUSIC (MC-MUSIC) and rank and trace minimization (RTM) algorithms, the proposed method can suppress the non-uniform noise considerably, and improve the DOA estimation performance significantly in the case of the coherent signals.