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Communication dans un congrès

Dispersive grid-free algorithm applied on real data for modal estimation in ocean acoustics

Thomas Paviet Clément Dorffer 1 Julien Bonnel 2 Barbara Nicolas 3 Thierry Chonavel 4, 5 Angélique Drémeau 1
1 Lab-STICC_ENSTAB_CID_TOMS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
3 Imagerie Ultrasonore
CREATIS - Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé
5 Lab-STICC_IMTA_CID_TOMS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : In underwater acoustics, shallow-water environments (depth < 200 m) act as modal dispersive waveguides for low frequency sources (f < 250 Hz). Then the signal can be described as a sum of few modal components, each mode propagating with its own wavenumber. A good estimation of those wavenumbers allows environment assessment or source localization. Considering a horizontal line array, a classical method to estimate wavenumber is the 2D Fourier transform, which requires however a long antenna to achieve good performance. In this study, we propose to take into account some physical priors to overcome those limitations. First, the small number of modal components motivates the use of a sparse representation. Different algorithms can be considered to recover the sparse model. Classically, they exploit a discretized wavenumber grid which can result in a lack of precision and be prejudicial for a fine characterization of the underlying physics. To remedy this defect, we propose then to insert a gradient-descent step in a greedy well-known procedure, that is the Orthogonal Matching Pursuit algorithm (OMP). Moreover, as a second physical prior, we also propose to integrate into the estimation procedure a general but robust dispersion relation that relates wavenumbers from one frequency to the next. The performance of the proposed method is validated using the Jaccard?s distance on simulated data, as well as real data acquired in the North Sea during a seismic campaign. It appears in particular more robust to noise or sensor number variations than other state-of-the-art algorithms such as the Bayesian approach proposed in previous work.
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https://hal.archives-ouvertes.fr/hal-03240218
Contributeur : Claude Inserra <>
Soumis le : vendredi 28 mai 2021 - 09:17:09
Dernière modification le : mercredi 21 juillet 2021 - 07:44:01

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Thomas Paviet, Clément Dorffer, Julien Bonnel, Barbara Nicolas, Thierry Chonavel, et al.. Dispersive grid-free algorithm applied on real data for modal estimation in ocean acoustics. e-Forum Acusticum 2020, Dec 2020, Lyon, France. pp.1989-1990, ⟨10.48465/fa.2020.0096⟩. ⟨hal-03240218⟩

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