Direction of arrival estimation for a non-ideal acoustic vector hydrophone array

•A new cost function is foumulated to achieve the DOA estimate.•The analytical expressions of the signal and axial angle bias matrix is derived.•The effectiveness of the proposed method is verifed by numerical simulation. In this article, to address the direction-of-arrival (DOA) estimation problem...

Full description

Saved in:

Bibliographic Details
Published in:	Applied acoustics Vol. 190; p. 108636
Main Authors:	Shi, Wentao, Li, Xiangshui, Wang, Weidong, Tan, Weijie, Li, Hui
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 15.03.2022
Subjects:	axial angle bias matrix Direction of arrival (DOA) estimation non-ideal acoustic vector hydrophone (AVH) array sparse alternating iterative minimization (SAIM) sparse alternating iterative minimization (SAIM) Direction of arrival (DOA) estimation axial angle bias matrix non-ideal acoustic vector hydrophone (AVH) array
ISSN:	0003-682X, 1872-910X
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	•A new cost function is foumulated to achieve the DOA estimate.•The analytical expressions of the signal and axial angle bias matrix is derived.•The effectiveness of the proposed method is verifed by numerical simulation. In this article, to address the direction-of-arrival (DOA) estimation problem via a non-ideal acoustic vector hydrophone (AVH) array, a sparse alternating iterative minimization (SAIM) method is proposed. First, a non-ideal AVH array model is established by introducing the axial angle bias parameter into the signal model. Then, to provide accurate DOA estimation, a new cost function is formulated based on a regularized weighted least squares to recovery the sparse signal and the axial angle bias matrix. In particular, to obtain the closed-form solutions of signal and axial angle bias matrix, the Majorization-minimization algorithm is employed to turn the penalty term with a user parameter optimization problem into the weighted Frobenius norm one. In each iteration, to achieve more accurate DOA estimation, the desired axial angle bias matrix is reconstructed based on the distribution characteristics of axial angle bias parameter in the matrix. Extensive numerical simulation and experimental results show that the DOA estimation performance of the proposed method is superior to several well-known methods for a non-ideal AVH array.
ISSN:	0003-682X 1872-910X
DOI:	10.1016/j.apacoust.2022.108636