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dc.contributor.authorFantacci, C.
dc.contributor.authorVo, Ba-Ngu
dc.contributor.authorVo, Ba Tuong
dc.contributor.authorBattistelli, G.
dc.contributor.authorChisci, L.
dc.date.accessioned2018-05-18T07:58:14Z
dc.date.available2018-05-18T07:58:14Z
dc.date.created2018-05-18T00:23:15Z
dc.date.issued2018
dc.identifier.citationFantacci, C. and Vo, B. and Vo, B.T. and Battistelli, G. and Chisci, L. 2018. Robust Fusion for Multisensor Multiobject Tracking. IEEE Signal Processing Letters. 25 (5): pp. 640-644.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/67376
dc.identifier.doi10.1109/LSP.2018.2811750
dc.description.abstract

This letter proposes analytical expressions for the fusion of certain classes of labeled multiobject densities via Kullback-Leibler averaging. Specifically, we provide analytical fusion rules for the labeled multi-Bernoulli and marginalized d-generalized labeled multi-Bernoulli families of labeled multiobject densities. Information fusion via Kullback-Leibler averaging ensures immunity to double counting of information and is essential to the development of effective multiagent multiobject estimation.

dc.publisherInstitute of Electrical and Electronics Engineers
dc.titleRobust Fusion for Multisensor Multiobject Tracking
dc.typeJournal Article
dcterms.source.volume25
dcterms.source.number5
dcterms.source.startPage640
dcterms.source.endPage644
dcterms.source.issn1070-9908
dcterms.source.titleIEEE Signal Processing Letters
curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Science (EECMS)
curtin.accessStatusFulltext not available


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