Benoit Oudompheng

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Recent developments in shallow water ocean acoustic tomography propose the use of an original configuration composed of two source-receiver vertical arrays and wideband sources. The recording space thus has three dimensions, with two spatial dimensions and the frequency dimension. Using this recording space, it is possible to build a three-dimensional (3D)(More)
In this paper, we propose a method for moving-source localization based on beamforming output and on sparse representation of the source positions. The goal of this method is to achieve spatial deconvolution of the beamforming, to provide accurate source localization for pass-by experiments. To perform this deconvolution, we use a smooth approximation of(More)
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 ℓ1/ℓ2 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(More)
This paper presents a new frequency method for blind separation of mixtures of scaled and delayed versions of sources. This kind of problem can occur in air and underwater acoustics. By assuming the mutual independence of the sources, we make use of the power spectral densities and the cross power spectral densities of mixed data to estimate the sources,(More)
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