Off-Grid DOA Estimation Based on Alternating Iterative Weighted Least Squares for Acoustic Vector Hydrophone Array

In this paper, an alternating iterative weighted least squares method is proposed to handle the off-grid issue in sparsity-based direction of arrival (DOA) estimation for acoustic vector hydrophone (AVH) array. Firstly, the off-grid model via AVH array is formulated by introducing a bias parameter into the signal model. Secondly, the reconstructed interference plus noise covariance matrix is calculated as the weighting term. Then, a novel objective function with respect to the sparse signal and the unknown bias parameter is developed based on weighted least squares. Finally, the closed-form solutions of the sparse signal and the unknown bias parameter are deduced. Simulation results reveal that compared with the state-of-the-art algorithms, the proposed method improves the DOA estimation accuracy in the presence of a coarse sample grid and has a faster convergence speed. Furthermore, the effectiveness and robustness of the proposed method are verified by the underwater experimental results.