Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.dsp.2009.08.011
Title: Interacting MCMC particle filter for tracking maneuvering target
Authors: Jing, L.
Vadakkepat, P. 
Keywords: Maneuvering target tracking
Markov chain Monte Carlo
Particle filter
Particle swarm
Issue Date: Mar-2010
Source: Jing, L., Vadakkepat, P. (2010-03). Interacting MCMC particle filter for tracking maneuvering target. Digital Signal Processing: A Review Journal 20 (2) : 561-574. ScholarBank@NUS Repository. https://doi.org/10.1016/j.dsp.2009.08.011
Abstract: In this paper, a new method, named interacting MCMC particle filter, is proposed to track maneuvering target. The particles are sampled from the target posterior distribution via direct interacting MCMC sampling method, which avoids sample impoverishment and increases the robustness of the algorithm. Moreover, the interacting MCMC particle filter algorithm accelerates the MCMC convergence rate via propagating each particle based on both its history information and the information from other particles. © 2009 Elsevier Inc. All rights reserved.
Source Title: Digital Signal Processing: A Review Journal
URI: http://scholarbank.nus.edu.sg/handle/10635/56361
ISSN: 10512004
DOI: 10.1016/j.dsp.2009.08.011
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