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arXiv · 1604.03450

A Noise-Robust Method with Smoothed \ell_1/\ell_2 Regularization for Sparse Moving-Source Mapping

Mai Quyen Pham·Benoit Oudompheng·Jérôme I. Mars·Barbara Nicolas
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Abstract

The method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced with a smooth \ell_1/\ell_2 regularization term. As the mean of the noise in the power spectrum domain is dependent on its variance in the time domain, the proposed method includes a variance estimation step, which allows more robust blind deconvolution. Validation of the method on both simulated and real data, and of its performance, are compared with two well-known methods from the literature: the deconvolution approach for the mapping of acoustic sources, and sound density modeling.

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Mai Quyen Pham, Benoit Oudompheng, Jérôme I. Mars, Barbara Nicolas. 2016-04-01. A Noise-Robust Method with Smoothed \ell_1/\ell_2 Regularization for Sparse Moving-Source Mapping. https://arxiv.org/abs/1604.03450

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