Distributed Monte Carlo information fusion and distributed particle filtering

Isaac L. Manuel, Adrian N. Bishop

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    8 Citations (Scopus)

    Abstract

    We present a Monte Carlo solution to the distributed data fusion problem and apply it to distributed particle filtering. The consensus-based fusion algorithm is iterative and it involves the exchange and fusion of empirical posterior densities between neighbouring agents. As the fusion method is Monte Carlo based it is naturally applicable to distributed particle filtering. Furthermore, the fusion method is applicable to a large class of networks including networks with cycles and dynamic topologies. We demonstrate both distributed fusion and distributed particle filtering by simulating the algorithms on randomly generated graphs.

    Original languageEnglish
    Title of host publication19th IFAC World Congress IFAC 2014, Proceedings
    EditorsEdward Boje, Xiaohua Xia
    PublisherIFAC Secretariat
    Pages8681-8688
    Number of pages8
    ISBN (Electronic)9783902823625
    DOIs
    Publication statusPublished - 2014
    Event19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014 - Cape Town, South Africa
    Duration: 24 Aug 201429 Aug 2014

    Publication series

    NameIFAC Proceedings Volumes (IFAC-PapersOnline)
    Volume19
    ISSN (Print)1474-6670

    Conference

    Conference19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014
    Country/TerritorySouth Africa
    CityCape Town
    Period24/08/1429/08/14

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