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dc.contributor.authorBryant, D.
dc.contributor.authorVo, Ba Tuong
dc.contributor.authorVo, Ba-Ngu
dc.contributor.authorJones, B.
dc.date.accessioned2018-12-13T09:13:22Z
dc.date.available2018-12-13T09:13:22Z
dc.date.created2018-12-12T02:46:41Z
dc.date.issued2018
dc.identifier.citationBryant, D. and Vo, B.T. and Vo, B. and Jones, B. 2018. A generalized labeled multi-bernoulli filter with object spawning. IEEE Transactions on Signal Processing. 66 (23): pp. 6177-6189.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/72442
dc.identifier.doi10.1109/TSP.2018.2872856
dc.description.abstract

Previous labeled random finite set filter developments use a motion model that only accounts for survival and birth. While such a model provides the means for a multi-object tracking filter, such as the generalized labeled multi-Bernoulli (GLMB) filter to capture object births and deaths in a wide variety of applications, it lacks the capability to capture spawned tracks and their lineages. In this paper, we propose a new Generalized Labeled Multi-Bernoulli (GLMB)-based filter that formally incorporates spawning, in addition to birth. This formulation enables the joint estimation of a spawned object's state and information regarding its lineage. Simulations results demonstrate the efficacy of the proposed formulation.

dc.publisherIEEE
dc.titleA generalized labeled multi-bernoulli filter with object spawning
dc.typeJournal Article
dcterms.source.volume66
dcterms.source.number23
dcterms.source.startPage6177
dcterms.source.endPage6189
dcterms.source.issn1053-587X
dcterms.source.titleIEEE Transactions on Signal Processing
curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Science (EECMS)
curtin.accessStatusFulltext not available


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