On the Design of Low-Rank Differential Beamformers with Nonuniform Linear Microphone Arrays

Kronecker product beamforming is an effective technique for designing beamformers with nonuniform linear arrays (NULAs). However, current techniques are restricted to NULAs with specific configurations, where the steering vector of the array is represented as a Kronecker product of steering vectors from smaller virtual arrays. This paper overcomes these constraints by proposing a novel approach to designing Kronecker product beamformers for NULAs from a low-rank perspective. Our approach involves decomposing the NULA into overlapping subarrays and organizing the sensor signals from these subarrays into a matrix. We then apply filters to both sides of this matrix to produce an output, which is then converted into a low-rank beamforming process. This method is highly adaptable and can be utilized for NULAs with any number of microphones.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10889353
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
0.00

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article

On the Design of Low-Rank Differential Beamformers with Nonuniform Linear Microphone Arrays

Hanchen Pei, Gongping Huang, Jingdong Chen, Jacob Benesty et al.
Speech and Audio Processing
article

On the Design of Low-Rank Differential Beamformers with Nonuniform Linear Microphone Arrays

Hanchen Pei, Gongping Huang, Jingdong Chen, Jacob Benesty, Jilu Jin, Kang Chen
article en

Abstract

Kronecker product beamforming is an effective technique for designing beamformers with nonuniform linear arrays (NULAs). However, current techniques are restricted to NULAs with specific configurations, where the steering vector of the array is represented as a Kronecker product of steering vectors from smaller virtual arrays. This paper overcomes these constraints by proposing a novel approach to designing Kronecker product beamformers for NULAs from a low-rank perspective. Our approach involves decomposing the NULA into overlapping subarrays and organizing the sensor signals from these subarrays into a matrix. We then apply filters to both sides of this matrix to produce an output, which is then converted into a low-rank beamforming process. This method is highly adaptable and can be utilized for NULAs with any number of microphones.

Université du Québec à Montréal (CA), Northwestern Polytechnical University (CN), Wuhan University (CN), Institut National de la Recherche Scientifique (CA)
National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 96%
Speech and Audio Processing
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On the Design of Low-Rank Differential Beamformers with Nonuniform Linear Microphone Arrays — Hanchen Pei, Gongping Huang, et al. · (2025) | TGRS Research Map | TGRS