Direction of arrival estimation of acoustic vector sensor array based on the combined information processing of pressure and particle velocity using covariance matrix decomposition

A combined processing method of pressure and particle velocity (PV-CPM) for acoustic vector sensor array using covariance matrix decomposition (CMD) is proposed. In this method, the cross-covariance matrix of pressure and particle velocity is decomposed into an observation angle coefficient matrix and a residual covariance matrix. To avoid choosing the observation angle, the coefficient matrix is combined with the guidance vector. By adopting the singular value decomposition, the residual covariance matrix is reconstructed into the new Hermitian covariance matrix, which is ultimately used to implement the MVDR beamforming method. Theoretical analysis shows that the new covariance matrix can achieve higher array processing gain. Furthermore, the numerical simulation proves that the computational complexity of the proposed method is similar to that of the Nehorai’s method, but its array processing gain and multi-target resolution are higher than those of the traditional PV-CPM.