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오현동

Oh, Hyondong
Autonomous Systems Lab.
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dc.citation.endPage 616 -
dc.citation.number 4 -
dc.citation.startPage 605 -
dc.citation.title IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS -
dc.citation.volume 47 -
dc.contributor.author Ding, Runxiao -
dc.contributor.author Yu, Miao -
dc.contributor.author Oh, Hyondong -
dc.contributor.author Chen, Wen-Hua -
dc.date.accessioned 2023-12-21T22:20:05Z -
dc.date.available 2023-12-21T22:20:05Z -
dc.date.created 2017-05-08 -
dc.date.issued 2017-04 -
dc.description.abstract This paper proposes an environment-dependent vehicle dynamic modeling approach considering interactions between the noisy control input of a dynamic model and the environment in order to make best use of domain knowledge. Based on this modeling, a new domain knowledge-aided moving horizon estimation (DMHE) method is proposed for ground moving target tracking. The proposed method incorporates different types of domain knowledge in the estimation process considering both environmental physical constraints and interaction behaviors between targets and the environment. Furthermore, in order to deal with a data association ambiguity problem of multiple-target tracking in a cluttered environment, the DMHE is combined with a multiple-hypothesis tracking structure. Numerical simulation results show that the proposed DMHE-based method and its extension could achieve better performance than traditional tracking methods which utilize no domain knowledge or simple physical constraint information only. -
dc.identifier.bibliographicCitation IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, v.47, no.4, pp.605 - 616 -
dc.identifier.doi 10.1109/TSMC.2016.2615188 -
dc.identifier.issn 2168-2216 -
dc.identifier.scopusid 2-s2.0-85017589860 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/21927 -
dc.identifier.url http://ieeexplore.ieee.org/document/7707385/ -
dc.identifier.wosid 000398966700003 -
dc.language 영어 -
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC -
dc.title New Multiple-Target Tracking Strategy Using Domain Knowledge and Optimization -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.relation.journalWebOfScienceCategory Automation & Control Systems; Computer Science, Cybernetics -
dc.relation.journalResearchArea Automation & Control Systems; Computer Science -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Domain knowledge -
dc.subject.keywordAuthor force-based model -
dc.subject.keywordAuthor moving horizon estimation (MHE) -
dc.subject.keywordAuthor multiple-hypothesis tracking (MHT) -
dc.subject.keywordAuthor multiple-target tracking (MTT) -
dc.subject.keywordPlus SOCIAL FORCE MODEL -
dc.subject.keywordPlus STATE ESTIMATION -
dc.subject.keywordPlus DATA ASSOCIATION -
dc.subject.keywordPlus CONSTRAINTS -
dc.subject.keywordPlus FILTERS -
dc.subject.keywordPlus PERFORMANCE -
dc.subject.keywordPlus SYSTEMS -

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