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Batch Processing through Particle Swarm Optimization for Target Motion Analysis with Bottom Bounce Underwater Acoustic Signals

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dc.contributor.authorOh, Raegeun-
dc.contributor.authorSong, Taek Lyul-
dc.contributor.authorChoi, Jee Woong-
dc.date.accessioned2021-06-22T09:08:08Z-
dc.date.available2021-06-22T09:08:08Z-
dc.date.issued2020-02-
dc.identifier.issn1424-8220-
dc.identifier.issn1424-3210-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/1320-
dc.description.abstractA target angular information in 3-dimensional space consists of an elevation angle and azimuth angle. Acoustic signals propagating along multiple paths in underwater environments usually have different elevation angles. Target motion analysis (TMA) uses the underwater acoustic signals received by a passive horizontal line array to track an underwater target. The target angle measured by the horizontal line array is, in fact, a conical angle that indicates the direction of the signal arriving at the line array sonar system. Accordingly, bottom bounce paths produce inaccurate target locations if they are interpreted as azimuth angles in the horizontal plane, as is commonly assumed in existing TMA technologies. Therefore, it is necessary to consider the effect of the conical angle on bearings-only TMA (BO-TMA). In this paper, a target conical angle causing angular ambiguity will be simulated using a ray tracing method in an underwater environment. A BO-TMA method using particle swarm optimization (PSO) is proposed for batch processing to solve the angular ambiguity problem.-
dc.format.extent14-
dc.language영어-
dc.language.isoENG-
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)-
dc.titleBatch Processing through Particle Swarm Optimization for Target Motion Analysis with Bottom Bounce Underwater Acoustic Signals-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/s20041234-
dc.identifier.scopusid2-s2.0-85079840296-
dc.identifier.wosid000522448600285-
dc.identifier.bibliographicCitationSensors, v.20, no.4, pp 1 - 14-
dc.citation.titleSensors-
dc.citation.volume20-
dc.citation.number4-
dc.citation.startPage1-
dc.citation.endPage14-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaInstruments & Instrumentation-
dc.relation.journalWebOfScienceCategoryChemistry, Analytical-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryInstruments & Instrumentation-
dc.subject.keywordPlusBEARINGS-
dc.subject.keywordPlusTRACKING-
dc.subject.keywordPlusOBSERVABILITY-
dc.subject.keywordPlusOCEAN-
dc.subject.keywordAuthortarget motion analysis-
dc.subject.keywordAuthorbottom bounce path-
dc.subject.keywordAuthorray tracing-
dc.subject.keywordAuthorparticle swarm optimization-
dc.identifier.urlhttps://www.mdpi.com/1424-8220/20/4/1234-
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ERICA 첨단융합대학 (ERICA 지능정보양자공학전공)
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