Sparsity-based localization of spatially coherent distributed sources

Abstract : In this paper, the localization of spatially distributed sources is considered. Based on the problem formulation of the De-convolution Approach for the Mapping of Acoustic Sources (DAMAS), a criterion based on a convex optimization under sparsity constraint is proposed to locate the sources. Also an original method is given to recover the angular distributions and the power of the sources. Simulations executed in the scenario of a mixture of distributed and point sources illustrate the validation of the proposed approach compared to other methods.
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Wenmeng Xiong, José Picheral, Sylvie Marcos, Gilles Chardon. Sparsity-based localization of spatially coherent distributed sources. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Mar 2016, Shanghai, China. ⟨10.1109/ICASSP.2016.7472276⟩. ⟨hal-01231789⟩

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