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Undersea target classification using canonical correlation analysis

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dc.contributor.authorScharf, Louis L., author
dc.contributor.authorAzimi-Sadjadi, Mahmood R., author
dc.contributor.authorPezeshki, Ali, author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2007-01-03T04:18:51Z
dc.date.available2007-01-03T04:18:51Z
dc.date.issued2007
dc.description.abstractCanonical correlation analysis is employed as a multiaspect feature extraction method for underwater target classification. The method exploits linear dependence or coherence between two consecutive sonar returns, at different aspect angles. This is accomplished by extracting the dominant canonical correlations between the two sonar returns and using them as features for classifying mine-like objects from nonmine-like objects. The experimental results on a wideband acoustic backscattered data set, which contains sonar returns from several mine-like and nonmine-like objects in two different environmental conditions, show the promise of canonical correlation features for mine-like versus nonmine-like discrimination. The results also reveal that in a fixed bottom condition, canonical correlation features are relatively invariant to changes in aspect angle.
dc.description.sponsorshipThis work was supported by the U.S. Office of Naval Research (ONR) under Contracts N00014-02-1-0006 and N00014-04-1-0084.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationPezeshki, Ali, Mahmood R. Azimi-Sadjadi, and Louis L. Scharf, Undersea Target Classification Using Canonical Correlation Analysis, IEEE Journal of Oceanic Engineering 32, no. 4 (October 2007): 948-955.
dc.identifier.urihttp://hdl.handle.net/10217/994
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©2007 IEEE.
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectunderwater target classification
dc.subjectmultiaspect feature extraction
dc.subjectlinear dependence and coherence
dc.subjectcanonical correlations
dc.titleUndersea target classification using canonical correlation analysis
dc.typeText

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