Deconvolution beamforming based on a fast gradient algorithm for sound source localization

Autor: Ming Zan, Zhongming Xu, Zhifei Zhang, Zhonghua Tang, Linsen Huang
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Journal of Low Frequency Noise, Vibration and Active Control, Vol 42 (2023)
Druh dokumentu: article
ISSN: 1461-3484
2048-4046
14613484
88484572
DOI: 10.1177/14613484221136047
Popis: Deconvolution beamforming has gotten increased attention as a way to improve the spatial resolution of delay-and-sum beamforming. It has the ability to decrease sidelobes and increase resolution. However, compared to conventional beamforming, the extra computation of the deconvolution method is a drawback. A more efficient approach is developed to improve the computing speed of the deconvolution method. Specifically, when tackling deconvolution problems, this method improves computational performance by combining Fourier operation with a fast gradient algorithm called the double momentum gradient algorithm. We compare the proposed method with two known effective deconvolution methods, namely the fast Fourier transform non-negative least squares algorithm and the fast iterative shrinkage threshold algorithm. The results of simulation and experiment reveal that the proposed method tends to give a better spatial resolution within a short computational time and is more suitable for engineering applications.
Databáze: Directory of Open Access Journals
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