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Particle filtering in high-dimensional systems with Gaussian approximations

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

10 Scopus citations

Abstract

In this paper we introduce a new multiple particle filtering approach for problems where the state-space of the system is of highdimension. We propose to break the space into subspaces and to perform separate particle filtering in each of them. The two critical operations of particle filtering, the particle propagation and weight computation of each particle filter are performed wherever necessary with the aid of parametric distributions received from other subspaces. The proposed method is demonstrated by computer simulations and the results show an excellent performance when compared to other implementations of multiple particle filtering.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages8013-8017
Number of pages5
ISBN (Print)9781479928927
DOIs
StatePublished - 2014
Event2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
Duration: May 4 2014May 9 2014

Publication series

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

Conference

Conference2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
Country/TerritoryItaly
CityFlorence
Period05/4/1405/9/14

Keywords

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

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