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Arthur Baggeroer. Watson, Jennifer Anne, 1973- Woods Hole Oceanographic Institution. Joint Program in Applied Ocean Physics and Engineering Woods Hole Oceanographic Institution Massachusetts Institute of Technology. Department of Ocean Engineering 2007-10-22T19:52:46Z 2007-10-22T19:52:46Z 2004 2004 http://hdl.handle.net/1721.1/39411 56356428 Thesis (Ph. D.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Ocean Engineering; and, the Woods Hole Oceanographic Institution), 2004. Includes bibliographical references (v. 2, leaves 211-215). In recent years the focus of passive detection and localization of submarines has moved from the deep ocean into the littoral regions. the problem of passive detection in these regions is complicated by strong multipath propagation with high transmission loss. Large aperture planar arrays have the potential to improve detection performance due to their high resolution and high gain, but are suceptible to two main performance degradation mechanisms: limited spatial coherence of signals and nonstationarity of high bearing rate interference sources common in littoral regions of strategic importance. This thesis presents subarray processing as a method of improving passive detection performance using such large arrays. This thesis develops statistical models for the detection of performance of three adaptive, sample-covariance-based subarray processing algorithms which incorporate the effects of limited spatial coherence as well as finite snapshot support. The performance of the optimum processor conditioned on known data coveriances is derived as well for comparison. These models are then used to compare subarray algorithms and partitioning schemes in a variety of interference environments using plane wave and matched-field propagation models. (cont.) The analysis shows a tradeoff between the required adaptive degrees of freedom, snapshot support, and adaptive resolution. This thesis shows that for both plane-wave and matched-field processing, the Conventional-Then-Adaptive (CTA) algorithm optimizes this tradeoff most efficiently. Finally, a comparison of the CTA algorithm to beam-space adaptive processing shows that for moderate beam coverage, the subarray algorithm performs as well as or superior to the adaptive beamspace algorighm. by Jennifer Anne Watson. Ph.D. 2 v. (215 leaves) eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 /Woods Hole Oceanographic Institution. Joint Program in Applied Ocean Science and Engineering. Ocean Engineering. Woods Hole Oceanographic Institution. GC7.1 .W37 2004 Sonar Performance analysis of subaperture processing using a large aperture planar towed array Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="65d52bc7-29bf-41cd-80ec-d92b90a9ade9"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Performance analysis of subaperture processing using a large aperture planar towed array</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2004</PublicationDate> <Authors> <Author> <DisplayName>Watson, Jennifer Anne, 1973-</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>/Woods Hole Oceanographic Institution. Joint Program in Applied Ocean Science and Engineering.</Keyword> <Keyword>Ocean Engineering.</Keyword> <Keyword>Woods Hole Oceanographic Institution.</Keyword> <Abstract>In recent years the focus of passive detection and localization of submarines has moved from the deep ocean into the littoral regions. the problem of passive detection in these regions is complicated by strong multipath propagation with high transmission loss. Large aperture planar arrays have the potential to improve detection performance due to their high resolution and high gain, but are suceptible to two main performance degradation mechanisms: limited spatial coherence of signals and nonstationarity of high bearing rate interference sources common in littoral regions of strategic importance. This thesis presents subarray processing as a method of improving passive detection performance using such large arrays. This thesis develops statistical models for the detection of performance of three adaptive, sample-covariance-based subarray processing algorithms which incorporate the effects of limited spatial coherence as well as finite snapshot support. The performance of the optimum processor conditioned on known data coveriances is derived as well for comparison. These models are then used to compare subarray algorithms and partitioning schemes in a variety of interference environments using plane wave and matched-field propagation models.</Abstract> <Abstract>(cont.) The analysis shows a tradeoff between the required adaptive degrees of freedom, snapshot support, and adaptive resolution. This thesis shows that for both plane-wave and matched-field processing, the Conventional-Then-Adaptive (CTA) algorithm optimizes this tradeoff most efficiently. Finally, a comparison of the CTA algorithm to beam-space adaptive processing shows that for moderate beam coverage, the subarray algorithm performs as well as or superior to the adaptive beamspace algorighm.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>