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Tracking a maneuvering target in clutter by a new smoothing particle filter

  • Yanqiu Li*
  • , Yi Shen
  • , Zhiyan Liu
  • , Ping He
  • *Corresponding author for this work
  • Harbin Institute of Technology

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

Abstract

Tracking maneuvering target in cluttered environment is a problem of great theoretical and application interest. In this paper a new smoothing particle filer algorithm is proposed which combines the particle filter with a Gibbs sampler to perform the smoothing of the estimation of the target maneuvering and measurement origin. This algorithm is used to estimate states of a maneuvering target from its cluttered measurements, and the simulation results show its powerful ability to solve the problem.

Original languageEnglish
Title of host publicationIMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference
Pages843-848
Number of pages6
DOIs
StatePublished - 2005
EventIMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference - Ottawa, ON, Canada
Duration: 16 May 200519 May 2005

Publication series

NameConference Record - IEEE Instrumentation and Measurement Technology Conference
Volume2
ISSN (Print)1091-5281

Conference

ConferenceIMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference
Country/TerritoryCanada
CityOttawa, ON
Period16/05/0519/05/05

Keywords

  • Gibbs sampler
  • Maneuvering target tracking
  • Nonlinear/non-Gaussian model
  • Particle filters

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