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  4. COARRAY MANIFOLD SEPARATION IN THE SPHERICAL HARMONICS DOMAIN FOR ENHANCED SOURCE LOCALIZATION
 
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COARRAY MANIFOLD SEPARATION IN THE SPHERICAL HARMONICS DOMAIN FOR ENHANCED SOURCE LOCALIZATION

Source
ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings
ISSN
15206149
Date Issued
2022-01-01
Author(s)
Yadav, Shekhar Kumar
George, Nithin V.  
DOI
10.1109/ICASSP43922.2022.9747851
Volume
2022-May
Abstract
The order of a three-dimensional wavefield captured by a spherical array is limited by the number of sampling points i.e. the number of sensors in the array. This restricts the source localization performance of existing techniques for a spherical array. In this paper, we introduce the concept of difference coarray to spherical arrays and propose an algorithm which utilises the increased degrees-of-freedom (DOF) provided by the virtual coarray sensors to perform enhanced source localization. We make use of coarray manifold separation in the spherical harmonics domain to generate a Vandermonde structured coarray manifold matrix which allows us to propose a novel subspace-based algorithm, which we call the coarraySH-MUSIC. We also introduce a polynomial rooting version of our algorithm which does not rely on extensive grid searches. The proposed algorithms are evaluated using various simulated experiments on source localization.
Unpaywall
URI
http://repository.iitgn.ac.in/handle/IITG2025/26259
Subjects
Difference Coarray | MUSIC | Source Localization | Spatial Smoothing | Spherical Array | Spherical Harmonics
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