A particle filtering approach to constrained motion estimation in tracking multiple targets

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Particle filtering has been successfully used in complex target tracking applications such as multiple target tracking. The particle filter can be used to incorporate constraints on target motion to improve tracking performance; this can be achieved using likelihood functions and sampling distributions. In this paper, we propose the constraint likelihood function independent partitions (CLIP) algorithm that uses constraints on target motion. This is achieved by incorporating a constraint likelihood function with the particle weights. As demonstrated by our simulations, a higher increase in tracking performance is obtained with our proposed constrained motion proposal (COMP) algorithm that incorporates target kinematic constraint information directly into the proposal density of the particle filter.

Original languageEnglish (US)
Title of host publicationConference Record of The Thirty-Ninth Asilomar Conference on Signals, Systems and Computers
Pages94-98
Number of pages5
StatePublished - Dec 1 2005
Event39th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Oct 28 2005Nov 1 2005

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2005
ISSN (Print)1058-6393

Other

Other39th Asilomar Conference on Signals, Systems and Computers
CountryUnited States
CityPacific Grove, CA
Period10/28/0511/1/05

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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    Kyriakides, I., Morrell, D., & Papandreou-Suppappola, A. (2005). A particle filtering approach to constrained motion estimation in tracking multiple targets. In Conference Record of The Thirty-Ninth Asilomar Conference on Signals, Systems and Computers (pp. 94-98). [1599709] (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2005).