2D DOA Estimation Algorithm by Nested Acoustic Vector-Sensor Array

• Published in: Circuits, systems, and signal processing Vol. 41; no. 2; pp. 1115 - 1130
• Main Authors: Liu, Sheng, Zhao, Jing, Zhang, Yu, Wu, Decheng
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2022; Springer Nature B.V
• Subjects: Algorithms; Circuits and Systems; Covariance matrix; Direction of arrival; Eigenvalues; Electrical Engineering; Electronics and Microelectronics; Engineering; Instrumentation; Mathematical analysis; Parameters; Sensor arrays; Signal,Image and Speech Processing; DOA estimation; Nested array; ESPRIT algorithm; AVS
• ISSN: 0278-081X; 1531-5878
• DOI: 10.1007/s00034-021-01831-5

In this paper, a two-dimensional direction-of-arrival (DOA) estimation algorithm based on nested acoustic vector-sensor (AVS) array is introduced. The minimum unit interval of the used nested AVS array is integral multiple of half-wavelength of signal. Firstly, four selection matrices are used to recombine four received vectors, by which four special cross-covariance matrices are obtained to form an extended block covariance matrix. Then, a set of parameters on elevation angles are estimated by traditional estimation of signal parameter via rotational invariance technique (ESPRIT) algorithm. Using these parameters, unambiguous elevation angles can be obtained without spectral peak search and added eigenvalue decomposition. At last, using the estimated elevation angles, the azimuth angles can be estimated by array manifold matching algorithm. The proposed algorithm can distinguish more signals than some existing ESPRIT algorithms. Many simulation results can prove the performance of the proposed algorithm in improving the accuracy of DOA estimation. Simulation results also show that the unit interval of optimal nested AVS array should be larger than half-wavelength of received signal.