Consensus‐based multiple‐model Bayesian filtering for distributed tracking

Giorgio Battistelli, Luigi Chisci, Claudio Fantacci, Alfonso Maria Farina, A. Graziano · IET Radar Sonar & Navigation · 2014

This study addresses distributed state estimation of jump Markovian systems and its application to tracking of a manoeuvring target by means of a network of heterogeneous sensors and communication nodes. Two novel consensus‐based multiple‐model filters are presented. Simulation experiments in a tracking case study, involving a strongly manoeuvring target and a sensor network characterised by weak connectivity, demonstrate the superiority of the proposed distributed multiple‐mode filters with respect to existing solutions.

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