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dc.contributor.authorNguyen, Tran Thien Dat
dc.contributor.authorKim, Du Yong
dc.date.accessioned2023-03-15T08:35:38Z
dc.date.available2023-03-15T08:35:38Z
dc.date.issued2019
dc.identifier.citationNguyen, T.T.D. and Kim, D.Y. 2019. GLMB tracker with partial smoothing. Sensors (Switzerland). 19 (20): ARTN 4419.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/91012
dc.identifier.doi10.3390/s19204419
dc.description.abstract

In this paper, we introduce a tracking algorithm based on labeled Random Finite Sets (RFS) and Rauch–Tung–Striebel (RTS) smoother via a Generalized Labeled Multi-Bernoulli (GLMB) multi-scan estimator to track multiple objects in a wide range of tracking scenarios. In the forward filtering stage, we use the GLMB filter to generate a set of labels and the association history between labels and the measurements. In the trajectory-estimating stage, we apply a track management strategy to eliminate tracks with short lifespan compared to a threshold value. Subsequently, we apply the information of trajectories captured from the forward GLMB filtering stage to carry out standard forward filtering and RTS backward smoothing on each estimated trajectory. For the experiment, we implement the tracker with standard GLMB filter, the hybrid track-before-detect (TBD) GLMB filter, and the GLMB filter with objects spawning. The results show improvements in tracking performance for all implemented trackers given negligible extra computational effort compared to standard GLMB filters.

dc.languageEnglish
dc.publisherMDPI
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/DP160104662
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectScience & Technology
dc.subjectPhysical Sciences
dc.subjectTechnology
dc.subjectChemistry, Analytical
dc.subjectEngineering, Electrical & Electronic
dc.subjectInstruments & Instrumentation
dc.subjectChemistry
dc.subjectEngineering
dc.subjectlabeled RFS
dc.subjectRTS smoother
dc.subjectGLMB filter
dc.subjectBEFORE-DETECT ALGORITHM
dc.subjectMULTI-BERNOULLI FILTER
dc.subjectRANDOM FINITE SETS
dc.subjectCPHD FILTER
dc.subjectIMPLEMENTATION
dc.subjectTIME
dc.subjectGLMB filter
dc.subjectRTS smoother
dc.subjectlabeled RFS
dc.titleGLMB tracker with partial smoothing
dc.typeJournal Article
dcterms.source.volume19
dcterms.source.number20
dcterms.source.issn1424-8220
dcterms.source.titleSensors (Switzerland)
dc.date.updated2023-03-15T08:35:33Z
curtin.departmentSchool of Elec Eng, Comp and Math Sci (EECMS)
curtin.accessStatusOpen access
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidNguyen, Tran Thien Dat [0000-0001-9185-4009]
curtin.identifier.article-numberARTN 4419
dcterms.source.eissn1424-8220
curtin.contributor.scopusauthoridKim, Du Yong [57193417073]
curtin.repositoryagreementV3


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