Study of Robust and High-gain Beamforming Based on Diagonal Reducing

Ocean ambient noise mainly includes uncorrelated noise and correlated noise. The uncorrelated noise only affects the diagonal elements in the noise covariance matrix, and it can be suppressed by subtracting a value on the diagonal elements. Utilizing this feature, a high array-gain beamforming based on diagonal reducing is presented. Meanwhile, the robustness becomes poor. So, the array weight norm constraint is used to ensure the robustness of this method, and the threshold is selected by some criterions. Then, the diagonal reducing value is calculated by the newton iteration method. After subtracting the diagonal reducing value, the covariance matrix is used in the minimum variance distortionless response (MVDR) beamformer. Both the numerical simulations and experimental results show that the proposed method can improve the array gain and the resolution capacity of multi-targets and it also can provide a tradeoff between array gain and robustness by changing the diagonal reducing value.