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Robust Target Tracking with Multi-Static Sensors under Insufficient TDOA Information

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dc.contributor.authorShin, Hyunhak-
dc.contributor.authorKu, Bonhwa-
dc.contributor.authorNelson, Jill K.-
dc.contributor.authorKo, Hanseok-
dc.date.accessioned2021-09-02T12:33:41Z-
dc.date.available2021-09-02T12:33:41Z-
dc.date.created2021-06-16-
dc.date.issued2018-05-
dc.identifier.issn1424-8220-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/76078-
dc.description.abstractThis paper focuses on underwater target tracking based on a multi-static sonar network composed of passive sonobuoys and an active ping. In the multi-static sonar network, the location of the target can be estimated using TDOA (Time Difference of Arrival) measurements. However, since the sensor network may obtain insufficient and inaccurate TDOA measurements due to ambient noise and other harsh underwater conditions, target tracking performance can be significantly degraded. We propose a robust target tracking algorithm designed to operate in such a scenario. First, track management with track splitting is applied to reduce performance degradation caused by insufficient measurements. Second, a target location is estimated by a fusion of multiple TDOA measurements using a Gaussian Mixture Model (GMM). In addition, the target trajectory is refined by conducting a stack-based data association method based on multiple-frames measurements in order to more accurately estimate target trajectory. The effectiveness of the proposed method is verified through simulations.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherMDPI-
dc.subjectPROBABILISTIC DATA ASSOCIATION-
dc.subjectPASSIVE RADAR-
dc.subjectLOCALIZATION-
dc.subjectPERFORMANCE-
dc.subjectFILTER-
dc.titleRobust Target Tracking with Multi-Static Sensors under Insufficient TDOA Information-
dc.typeArticle-
dc.contributor.affiliatedAuthorKu, Bonhwa-
dc.contributor.affiliatedAuthorKo, Hanseok-
dc.identifier.doi10.3390/s18051481-
dc.identifier.scopusid2-s2.0-85046655832-
dc.identifier.wosid000435580300180-
dc.identifier.bibliographicCitationSENSORS, v.18, no.5-
dc.relation.isPartOfSENSORS-
dc.citation.titleSENSORS-
dc.citation.volume18-
dc.citation.number5-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
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.keywordPlusPROBABILISTIC DATA ASSOCIATION-
dc.subject.keywordPlusPASSIVE RADAR-
dc.subject.keywordPlusLOCALIZATION-
dc.subject.keywordPlusPERFORMANCE-
dc.subject.keywordPlusFILTER-
dc.subject.keywordAuthormulti-static sonar-
dc.subject.keywordAuthorsonar tracking-
dc.subject.keywordAuthorsonar applications-
dc.subject.keywordAuthorMHT-
dc.subject.keywordAuthortree-search algorithms-
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