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A Multi-Scan Labeled Random Finite Set Model for Multi-Object State Estimation

dc.contributor.authorVo, Ba-Ngu
dc.contributor.authorVo, Ba-Tuong
dc.date.accessioned2023-03-09T08:20:30Z
dc.date.available2023-03-09T08:20:30Z
dc.date.issued2019
dc.identifier.citationVo, B.-N. and Vo, B.-T. 2019. A Multi-Scan Labeled Random Finite Set Model for Multi-Object State Estimation. IEEE Transactions on Signal Processing. 67 (19): pp. 4948-4963.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/90816
dc.identifier.doi10.1109/TSP.2019.2928953
dc.languageEnglish
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/DP170104854
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/DP160104662
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectScience & Technology
dc.subjectTechnology
dc.subjectEngineering, Electrical & Electronic
dc.subjectEngineering
dc.subjectState estimation
dc.subjectfiltering
dc.subjectsmoothing
dc.subjectrandom finite sets
dc.subjectmulti-dimensional assignment
dc.subjectGibbs sampling
dc.subjectBERNOULLI FILTER
dc.subjectEFFICIENT
dc.subjectTRACKING
dc.subjectAPPROXIMATION
dc.subjectCONVERGENCE
dc.subjectFUSION
dc.titleA Multi-Scan Labeled Random Finite Set Model for Multi-Object State Estimation
dc.typeJournal Article
dcterms.source.volume67
dcterms.source.number19
dcterms.source.startPage4948
dcterms.source.endPage4963
dcterms.source.issn1053-587X
dcterms.source.titleIEEE Transactions on Signal Processing
dc.date.updated2023-03-09T08:20:30Z
curtin.accessStatusOpen access
dcterms.source.eissn1941-0476


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