Open AccessNear‐Field Source Localization Using Spherical Microphone Arrays
Author(s) -
Huang Qinghua,
Zhang Guangfei,
Liu Kai
Publication year - 2016
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2016.01.024
Subject(s) - spherical harmonics , signal subspace , azimuth , microphone array , subspace topology , algorithm , signal (programming language) , range (aeronautics) , matrix (chemical analysis) , computer science , eigenvalues and eigenvectors , acoustics , mathematics , microphone , mathematical analysis , physics , telecommunications , geometry , artificial intelligence , noise (video) , engineering , materials science , sound pressure , composite material , quantum mechanics , image (mathematics) , programming language , aerospace engineering
A new method is proposed for joint range and bearing (azimuth and elevation) estimation of multiple near‐field acoustic sources using observations collected by a spherical microphone array. First, Spherical Fourier transform (SFT) is used to construct the array signal model in the spherical harmonics domain to decouple range and bearing information. Then the relation among the spherical harmonics of three adjacent degrees is exploited to build the recursive relationship of the signal subspace. Using Eigenvalue decomposition (EVD), bearings are estimated based on the eigenvalues and simultaneously the steering matrix can be represented by the signal subspace. Finally, range is estimated using the energy ratios of the elements of the steering matrix in the spherical harmonics domain. The algorithm can avoid parameter pairing and multi‐dimensional searching. It has lower computational complexity than that of the Multiple signal classification (MUSIC) method. The performance is evaluated by Monte‐Carlo simulations and the estimation root meansquare errors are compared to the corresponding Cramer‐Rao bounds (CRBs) and those of MUSIC range estimates, which demonstrate the validity of the proposed algorithm.