Direction finding via acoustic vector sensor array with non-orthogonal factors

This paper addresses the direction of arrival (DOA) estimation via an acoustic vector sensor (AVS) array in the presence of non-orthogonal factors. To mitigate the estimation bias, which is caused by non orthogonal factors, a novel DOA estimator is proposed by combining the iterative sparse maximum likelihood-based and maximum a posteriori (ISML-MAP) approaches. First, the two non-orthogonal AVS array models are formulated by introducing a perturbation parameter, based on which the DOA estimation bias is quantified for a single-source scenario. The results show that the non-orthogonal factor has a greater influence on the DOA estimation performance when the velocity sensor located in x-axis is selected as the reference sensor compared to the non-orthogonal AVS array model with the velocity sensor located in y-axis selected as the reference sensor. Then, the DOA of the acoustic source and the non-orthogonal deviation matrix (or angle deviation) are jointly estimated iteratively. In each iteration, three matrix rotation approaches are presented to determine the non-orthogonal deviation matrix. Simulation results demonstrated that the proposed methods achieve better DOA estimation performance than the existing methods for the non-orthogonal AVS array. (C) 2020 Elsevier Inc. All rights reserved.

Automated summary

This paper proposes a novel method for DOA estimation using an AVS array to reduce estimation bias caused by non-orthogonal factors. It is found that the influence of non-orthogonal factors on DOA estimation performance depends on the selection of the reference sensor. By jointly estimating the DOA of the acoustic source and the non-orthogonal deviation matrix, better DOA estimation performance is achieved.