基于协方差扩展PM算法的波达方向估计

针对基于传播算子方法(Propagator Method, PM)的水听器阵波达方向(Direction of Arrival, DOA)估计在低信噪比或者小快拍数时性能变差的问题，文章提出一种改进的基于PM算法的水听器阵方位估计方法。该方法利用信号子空间的旋转不变性特征对协方差矩阵进行扩展和重构，通过分块协方差矩阵的子矩阵得到传播算子矩阵。通过传播算子矩阵构造扩展噪声子空间，然后利用信号子空间与噪声子空间的正交性估计空间谱。仿真实验和湖上实验的结果表明：相较于传统PM方位估计算法，文中算法在低信噪比或者小快拍情况下具有较好的方位估计性能，在信噪比为0 dB时，文中方法比传统PM算法均方根误差减少0.6°；在快拍数为150时，比传统PM算法的均方根误差减少0.1°。

Direction of arrival estimation based on the covariance expanded PM algorithm

Due to the poor performance of the conventional propagator method (PM) algorithm based direction of arrival (DOA) estimation algorithm of hydrophone array in the case of low signal to noise ratio (SNR) or small number of snapshots, an improvement of this method is proposed in this paper. In this improved method, the covariance matrix is expanded and reconstructed by using the rotation invariance characteristics of the signal subspace, and the propagator matrix is obtained by the submatrices of the partitioned covariance matrix. The extended noise subspace is constructed by the propagator matrix, and then the spatial spectrum is estimated by using the orthogonality between the signal subspace and the noise subspace. The simulation and lake experimental results show that, the proposed method has better robust estimation performance in the cases of low SNR and small number of snapshots. Compared with conventional PM algorithm, the root mean square error (RMSE) of the proposed method is reduced by 0.6° when the SNR is 0 dB, and the RMSE of the proposed method is reduced by 0.1° when the number of snapshots is 150.