2014 American Control Conference 2014
DOI: 10.1109/acc.2014.6858896
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Distributed estimation using Bayesian consensus filtering

Abstract: Abstract-We present the Bayesian consensus filter (BCF) for tracking a moving target using a networked group of sensing agents and achieving consensus on the best estimate of the probability distributions of the target's states. Our BCF framework can incorporate nonlinear target dynamic models, heterogeneous nonlinear measurement models, non-Gaussian uncertainties, and higher-order moments of the locally estimated posterior probability distribution of the target's states obtained using Bayesian filters. If the… Show more

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Cited by 50 publications
(37 citation statements)
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“…Lemma 4 [16,17] The pdf P KL k ∈ Φ(X ) that globally minimizes the sum of KL divergences with the pdfs P i k for all agents is given by:…”
Section: Logarithmic Opinion Pool and Convergence Resultsmentioning
confidence: 99%
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“…Lemma 4 [16,17] The pdf P KL k ∈ Φ(X ) that globally minimizes the sum of KL divergences with the pdfs P i k for all agents is given by:…”
Section: Logarithmic Opinion Pool and Convergence Resultsmentioning
confidence: 99%
“…In contrast, we present a rigorous proof technique, which was first introduced in our prior work [17,18], for the LogOP scheme that is applicable for general probability distributions. This paper is organized as follows.…”
Section: Introductionmentioning
confidence: 99%
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