Title
Two-Stage Music With Reduced Spectrum Search For Spherical Arrays
Abstract
The multiple signal classification (MUSIC) algorithm is widely used in direction of arrival (DOA) estimation. Conventional MUSIC-like algorithms suffer from the heavy computational burden imposed by the two-dimensional (2-D) angle search and an exhaustive spectral search. We propose a two-stage unitary spherical harmonics MUSIC (TSU-SHMUSIC) that converts 2-D MUSIC into two new one-dimensional (1-D) MUSICs. The spherical harmonic steering vector is expressed in two forms, the linear weight of a uniform phase vector and the linear weight of a vector constructed by associated Legendre functions. These two expressions are used conjunction with Lagrange multiplier method to obtain two new corresponding search functions for the elevation and azimuth. We exploit the characteristics of real-valued spherical harmonics to construct virtual signals from the mirror directions of signal sources. A new noise subspace is computed from the covariance matrices of the virtual and real signals. We use this noise subspace to reduce the angle search ranges to half of the total angular field of view. The proposed methods have a considerably lower computational complexity than U-SHMUSIC. Numerical simulations demonstrate that the proposed methods provide perform better than the two-stage decoupled approach (TSDA). (C) 2020 Elsevier Inc. All rights reserved.
Year
DOI
Venue
2020
10.1016/j.dsp.2020.102836
DIGITAL SIGNAL PROCESSING
Keywords
DocType
Volume
Direction of arrival (DOA) estimation, Spherical harmonics MUSIC (SHMUSIC), Low complexity, Spectral search, Virtual signal
Journal
106
ISSN
Citations 
PageRank 
1051-2004
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Qinghua Huang130.75
Jiajun Feng200.34
Jingbiao Huang300.34
Yong Fang419131.43