Hybrid deconvolution separation methods based on matrix completion for multi-motion modes sound sources

Abstract

Beamforming techniques cannot effectively separate the mixed field of stationary and rotating sound sources. The issue becomes even more challenging when strong out-of-focus sources, e.g., stationary sources with rotating beamforming, are present, leading to a smearing effect and false localization results. The current algorithms for separating multiple moving sound sources have problems such as weak separation ability and complex computation. To more effectively address this challenge, two frequency domain hybrid deconvolution methods based on the virtual rotating array (VRA) and a matrix completion algorithm are proposed in this work. A matrix completion algorithm is used to establish the completed cross point spread function (C-PSF) matrix. Afterward, a linear equation system is constructed to separate the sound sources of different motion modes. Finally, the sound source separation localization problem is solved by Non-Negative Least-Squares (NNLS) and sparsity constraints deconvolution, respectively. The simulation and experimental results demonstrate that the proposed method can accurately locate and separate stationary and moving sound sources.