Convex optimization based robust adaptive beamforming for underwater sensor array

The existing adaptive beamforming techniques developed for underwater sensor array usually suffer from significant performance degradation due to the mismatch between the presumed and actual steering vectors. In this paper, a novel convex optimization based robust adaptive beamforming algorithm is proposed. First, the steering vector corresponding to the desired signal is estimated by solving a convex optimization problem constructed by the noise subspace and an introduced angular subspace. Second, another convex optimization problem based on spatial spectrum matching is solved to reconstruct the interference-plus-noise covariance matrix. Finally, the weight vector of robust adaptive beamforming is obtained using the minimum variance distortionless response method. Simulation and experiment results show that the proposed convex optimization based robust adaptive beamforming algorithm is robust against the steering vector mismatch and can achieve better performance than other existing RAB algorithms for the underwater sensor array.