Document Detail


Probabilistic PCA and Ocean Acoustic Tomography Inversion with an Adjoint Method.
MedLine Citation:
PMID:  18531135     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
We present an Ocean Acoustic Tomography (OAT) inversion in a shallow water environment. The idea is to determine the celerity c(z), z is depth, knowing the acoustic pressures caused by a multiple frequencies source and collected by a sparse receiver array. The variational approach minimizes a cost function which measures the adequacy between the measurements and their forward model equivalent. This method introduces also a regularisation term in the form (c(z)-c(b))(t)B(-1)(c(z)-c(b)), which supposes that c(z) follows an a priori normal law. To circumvent the problem of estimating B(-1), we propose to model the celerity vectors by a probabilistic PCA. In contrast to the methods which use PCA as a regularization method and filter the useful information, we take a sufficient number of axes which allow the modelization of useful information and filter only the noise. The probabilistic PCA introduces a reduced number of non correlated latent variables eta which act as new control parameters introduced in the cost function. This new regularization term, expressed as eta (t)eta, reduces the optimization computation time. In the following we apply the probabilistic PCA to an OAT problem, and present the results obtained when performing twin experiments.
Authors:
Mohamed Berrada; Fouad Badran; Sylvie Thiria
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  The Journal of the Acoustical Society of America     Volume:  123     ISSN:  1520-8524     ISO Abbreviation:  J. Acoust. Soc. Am.     Publication Date:  2008 May 
Date Detail:
Created Date:  2008-06-05     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7503051     Medline TA:  J Acoust Soc Am     Country:  United States    
Other Details:
Languages:  eng     Pagination:  3510     Citation Subset:  IM    
Affiliation:
Laboratoire d'Océanographie et du Climat - Expérimentation et Approches Numériques, Université Pierre et Marie Curie, Tour 45-55 - 5ème étage - 4, place Jussieu, 75005 Paris, France, mohamed.berrada@locean-ipsl.upmc.fr.
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