Tracking of coordinated groups using marginalised MCMC-based particle algorithm

François Septier, Sze Kim Pang, Simon Godsill, Avishy Carmi

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

22 Scopus citations


In this paper, we address the problem of detection and tracking of group and individual targets. In particular, we focus on a group model with a virtual leader which models the bulk or group parameter. To perform the sequential inference, we propose a Markov Chain Monte Carlo (MCMC)-based Particle algorithm with a marginalisation scheme using pairwise Kalman filters. Numerical simulations illustrate the ability of the algorithm to detect and track targets within groups, as well as infer both the correct group structure and the number of targets over time.

Original languageEnglish
Title of host publication2009 IEEE Aerospace Conference
StatePublished - 21 Sep 2009
Externally publishedYes
Event2009 IEEE Aerospace Conference - Big Sky, MT, United States
Duration: 7 Mar 200914 Mar 2009

Publication series

NameIEEE Aerospace Conference Proceedings
ISSN (Print)1095-323X


Conference2009 IEEE Aerospace Conference
Country/TerritoryUnited States
CityBig Sky, MT

ASJC Scopus subject areas

  • Aerospace Engineering
  • Space and Planetary Science


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