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Real-Time Sound Source Localization Based on the Ground-Reflection Compensation Algorithm

delete2026-09-08
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OA
AI
S
Shengkai Zhao
Z
Zhen Huang *
Z
Zhiwen Ma
Z
Zhengyang Zhang
Z
Zhenxin He
H
Hongjie Cheng *
DOI:10.3390/s26185685delete
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Abstract

Abstract

En 中文
Sound source localization based on microphone arrays has attracted extensive research interest in the fields of speech communication, detection and tracking. However, conventional near-field beamforming typically assumes free-field propagation and ignores coherent ground reflections, which bias phase estimates at floor-mounted arrays and degrade localization accuracy. To address this, the total Green’s function is reformulated by embedding the image-source reflected path directly into the beamforming propagation model. Unlike conventional approaches that assume free-field propagation, this formulation enables phase compensation to jointly account for the direct and ground-reflected wavefronts. The in-phase superposition of signals is then realized through frequency-domain phase compensation, and the sound source position is estimated via the maximum likelihood criterion. Subsequently, a dual-mode operation mechanism of automatic broadband scanning and manual single-frequency analysis is implemented, with frequency-weighted wideband spatial spectrum processing for noise and aliasing suppression. Finally, a real-time sound source localization system based on a 4 × 4 MEMS array is designed. Experimental results show that sound source localization in a broad frequency band can be achieved at standoff distances of 0.1 m–0.3 m from the array plane, with a localization accuracy of less than 0.015 m. The proposed method demonstrates strong robustness against ground-reflection interference and has potential applications in acoustic monitoring, industrial fault diagnosis and other related areas.
Keywords:
sound source localization
ground-reflection compensation
MEMS array
maximum likelihood estimation

Journal

Sensors cover
Sensors
IF:
3.5
Papers:
7.2W
Citations:
20.9W

Organization

R
Rocket Force University of Engineering
Scholars:
2.7K
Papers: 1.8K
Citations: 2
Cited Papers

Cited Papers

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errKujawski, Adam; Pelling, Art J. R.; Jekosch, Simon; Sarradj, Ennes
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