Introduces a principled decentralised possibilistic fusion rule proven asymptotically exact for the Bernoulli filter that maintains local posterior independence and outperforms probabilistic baselines in cardinality and localisation error.
Distributed Bernoulli filtering for target detection and tracking based on arithmetic average fusion
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Decentralised possibilistic inference with applications to target tracking
Introduces a principled decentralised possibilistic fusion rule proven asymptotically exact for the Bernoulli filter that maintains local posterior independence and outperforms probabilistic baselines in cardinality and localisation error.