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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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Abstract
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.
Keywords:
Sound localization
Deconvolution
beamforming
Three-dimensional
Variable -scale
Compressed computing grid