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Robust Fusion for Multisensor Multiobject Tracking
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DOI：10.1109/LSP.2018.2811750.png)
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Abstract
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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 delta-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.
Keywords:
Finite set statistics (FISST)
generalized labeled multi-Bernoulli (GLMB)
labeled multi-Bernoulli (LMB)
marginalized delta-GLMB (M delta-GLMB)
multiobject densities
random finite set (RFS)
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