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Conference Poster Year : 2015

Bayesian source localization with uncertain Green’s function

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Abstract

The localization of an acoustic source in the oceanic waveguide is a difficult task because the oceanic environment is often poorly known. Uncertainty in the environment results in uncertainty in the source position and poor localization results. Hence, localization methods dealing with environmental uncertainty are required. In this paper, a Bayesian approach to source localization is introduced in order to improve robustness and obtain quantitative measures of localization uncertainty. The Green’s function of the waveguide is considered as an uncertain random variable whose probability density accounts for environmental uncertainty. The uncertain distribution over range and depth is then obtained through the integration of the posterior probability density (PPD) over the Green’s function probability density. An efficient integration technique makes the whole localization process computationally efficient. Some results are presented for a simple uncertain Green’s function model to show the ability of the proposed method to give reliable PPDs.
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Dates and versions

hal-01156415 , version 1 (27-05-2015)

Identifiers

  • HAL Id : hal-01156415 , version 1

Cite

Yann Le Gall, Stan E. Dosso, François-Xavier Socheleau, Julien Bonnel. Bayesian source localization with uncertain Green’s function. OCEANS'15/MTS/IEEE, May 2015, Genova, Italy. , 2015. ⟨hal-01156415⟩
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