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Three-dimensional deconvolution beamforming based on the variable-scale compressed computing grid
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AI
DOI：10.1016/j.measurement.2022.112211.png)
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摘要
En 中文
In sound source localization, deconvolution beamforming has successfully improved the spatial resolution of conventional beamforming. However, the deconvolution method requires extra computation and more computing time. In three-dimensional space, the efficiency of the deconvolution method is low. Deconvolution with the compressed computing grid can reduce a lot of computing time. But the accuracy after compression will be limited to some extent. In this paper, a deconvolution method with the variable-scale compressed computing grid is proposed and verified. The algorithm can not only compress a certain number of grids but also guarantee accuracy. The simulation and experimental results show that the variable-scale compressed computing grid method has a certain improvement in computational efficiency and positioning accuracy.
Keyword:
Sound localization
Deconvolution
beamforming
Three-dimensional
Variable -scale
Compressed computing grid
期刊
IF:
5.6
论文数:
2.1W
被引数:
5.4W
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引用论文
分享收藏Improvement of Fourier-based fast iterative shrinkage-thresholding deconvolution algorithm for acoustic source identification.png)
APPLIED ACOUSTICS
APPLIED ACOUSTICSIF3.6
PREAI
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