@inproceedings{eb9f0153120848a2a3f4ffcdf994bf8f,
title = "Likelihood consensus: Principles and application to distributed particle filtering",
abstract = "We propose a distributed method for computing the joint (all-sensors) likelihood function (JLF) in a wireless sensor network. A consensus algorithm is used for a decentralized, iterative calculation of a sufficient statistic that describes an approximation to the JLF. After convergence of the consensus algorithm, the approximate JLF - which epitomizes the measurements of all sensors - is available at each sensor. This {"}likelihood consensus{"} method requires only communications between neighboring sensors. We implement the likelihood consensus method in a distributed particle filtering scheme. Each sensor runs a local particle filter that computes a global state estimate. The updating of the particle weights of each local particle filter uses the JLF. The performance of this distributed particle filter is demonstrated on a target tracking problem.",
keywords = "Bayesian estimation, consensus algorithm, distributed particle filter, target tracking, Wireless sensor network",
author = "Ondrej Hlinka and Ondrej Slu{\v c}iak and Franz Hlawatsch and Djuri{\'c}, \{Petar M.\} and Markus Rupp",
year = "2010",
doi = "10.1109/ACSSC.2010.5757533",
language = "English",
isbn = "9781424497218",
series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",
pages = "349--353",
booktitle = "Conference Record of the 44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010",
note = "44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010 ; Conference date: 07-11-2010 Through 10-11-2010",
}