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dc.contributor.authorPapp, Joseph C.  Concept link
dc.contributor.authorPreisig, James C.  Concept link
dc.contributor.authorMorozov, Andrey K.  Concept link
dc.date.accessioned2010-04-29T17:52:04Z
dc.date.available2010-04-29T17:52:04Z
dc.date.issued2010-04
dc.identifier.citationJournal of the Acoustical Society of America 127 (2010): 2385-2391en_US
dc.identifier.urihttps://hdl.handle.net/1912/3364
dc.descriptionAuthor Posting. © Acoustical Society of America, 2010. This article is posted here by permission of Acoustical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Acoustical Society of America 127 (2010): 2385-2391, doi:10.1121/1.3327799.en_US
dc.description.abstractMode filtering is most commonly implemented using the sampled mode shapes or pseudoinverse algorithms. Buck et al. [J. Acoust. Soc. Am. 103, 1813–1824 (1998)] placed these techniques in the context of a broader maximum a posteriori (MAP) framework. However, the MAP algorithm requires that the signal and noise statistics be known a priori. Adaptive array processing algorithms are candidates for improving performance without the need for a priori signal and noise statistics. A variant of the physically constrained, maximum likelihood (PCML) algorithm [A. L. Kraay and A. B. Baggeroer, IEEE Trans. Signal Process. 55, 4048–4063 (2007)] is developed for mode filtering that achieves the same performance as the MAP mode filter yet does not need a priori knowledge of the signal and noise statistics. The central innovation of this adaptive mode filter is that the received signal's sample covariance matrix, as estimated by the algorithm, is constrained to be that which can be physically realized given a modal propagation model and an appropriate noise model. Shallow water simulation results are presented showing the benefit of using the PCML method in adaptive mode filtering.en_US
dc.description.sponsorshipThis work was supported by the Office of Naval Research through ONR Grant Nos. N00014-05-10085 and N00014-06-10788 and through the WHOI Academic Programs Office.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.publisherAcoustical Society of Americaen_US
dc.relation.urihttps://doi.org/10.1121/1.3327799
dc.subjectAcoustic noiseen_US
dc.subjectAcoustic signal processingen_US
dc.subjectAdaptive filtersen_US
dc.subjectArray signal processingen_US
dc.subjectMaximum likelihood estimationen_US
dc.subjectUnderwater acoustic propagationen_US
dc.titlePhysically constrained maximum likelihood mode filteringen_US
dc.typeArticleen_US
dc.identifier.doi10.1121/1.3327799


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