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Multiple particle filtering with improved efficiency and performance

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

14 Scopus citations

Abstract

Particle filtering has been widely accepted as an important methodology for processing data represented by state-space models characterized by nonlinearities and/or non-Gaussianities. It is also well documented that particle filtering deteriorates quickly in performance when the dimension of the tracked state becomes large. This limits its application in many science/engineering problems. Previously we have proposed a way of alleviating this deficiency based on the use of multiple particle filtering. According to the approach, a number of particle filters are assigned to track different subsets of the state with time. In this paper, we propose a new method for accurate and efficient implementation of multiple particle filtering. We provide simulation results that demonstrate the performance of the new method.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4110-4114
Number of pages5
ISBN (Electronic)9781467369978
DOIs
StatePublished - Aug 4 2015
Event40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Brisbane, Australia
Duration: Apr 19 2014Apr 24 2014

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2015-August
ISSN (Print)1520-6149

Conference

Conference40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
Country/TerritoryAustralia
CityBrisbane
Period04/19/1404/24/14

Keywords

  • high-dimensional systems
  • multiple particle filtering
  • state-space models

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