Distributed filtering based on randomized gossip strategy

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

5 Scopus citations

Abstract

This paper formulates and studies the problem of distributed filtering based on randomized gossip strategy in order to estimate the state of a dynamic system via all sensors in a network. First we introduce the randomized gossip algorithm by which the fastest averaging strategy can be obtained for a network with an arbitrary topology. Then we combine the randomized gossip algorithm with the information filter to design a randomized gossip based distributed filtering algorithm. The proposed method can adopt different communication volume flexibly, which results in different estimation performance. This flexibility distinguishes our method from the existing ones. Simulation examples verify that our method outperforms the diffusion strategy based distributed filtering algorithm if a small increase of communication requirements is allowed.

Original languageEnglish
Title of host publicationMFI 2017 - 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages306-311
Number of pages6
ISBN (Electronic)9781509060641
DOIs
StatePublished - 7 Dec 2017
Event13th IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2017 - Daegu, Korea, Republic of
Duration: 16 Nov 201718 Nov 2017

Publication series

NameIEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
Volume2017-November

Conference

Conference13th IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2017
Country/TerritoryKorea, Republic of
CityDaegu
Period16/11/1718/11/17

Keywords

  • Dynamic system
  • Estimation fusion
  • Randomized gossip
  • Sensor networks

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