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    Physically constrained maximum likelihood mode filtering

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    JAS002385.pdf (516.6Kb)
    Date
    2010-04
    Author
    Papp, Joseph C.  Concept link
    Preisig, James C.  Concept link
    Morozov, Andrey K.  Concept link
    Metadata
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    Citable URI
    https://hdl.handle.net/1912/3364
    As published
    https://doi.org/10.1121/1.3327799
    DOI
    10.1121/1.3327799
    Keyword
     Acoustic noise; Acoustic signal processing; Adaptive filters; Array signal processing; Maximum likelihood estimation; Underwater acoustic propagation 
    Abstract
    Mode 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.
    Description
    Author 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.
    Collections
    • Applied Ocean Physics and Engineering (AOP&E)
    Suggested Citation
    Journal of the Acoustical Society of America 127 (2010): 2385-2391
     

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