Split augmented lagrange contraction deconvolution algorithm for sound source identification

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Journal of Vibration and Shock ›› 2020, Vol. 39 ›› Issue (23) : 141-148.

FAN Xiaopeng1, ZHANG Xin2,3, CHU Zhigang2,3, LI Li1

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Abstract

Here, a novel and efficient deconvolution algorithm with ultra-high resolution for sound source identification was proposed, it was called the split augmented Lagrange contraction deconvolution algorithm (SALCDA).In this method, the sparsity that the main sound source usually has and the idea of alternating directions for solving large-scale sparse recovery problems were used.Then a split variable equivalent to source strength was introduced into the mathematical model of beam forming deconvolution to establish the mathematical model of augmented Lagrange variable splitting for sound source identification.SALCDA was used to solve alternately and iteratively the split model, and gain the source strength.The results of simulation and tests showed that the source strength quantification ability of the proposed method is comparable to that of the classical deconvolution approach for mapping of acoustic sources (DAMAS); it has better convergence, ultra-high resolution within the whole analysis frequency range, and its iterative calculation speed is tens of times faster.

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sound source identification / sparse constrained deconvolution / split augmented Lagrange contraction algorithm (SALSA)

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FAN Xiaopeng1, ZHANG Xin2,3, CHU Zhigang2,3, LI Li1. Split augmented lagrange contraction deconvolution algorithm for sound source identification[J]. Journal of Vibration and Shock, 2020, 39(23): 141-148

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