Please use this identifier to cite or link to this item:
|Title:||Interacting MCMC particle filter for tracking maneuvering target|
|Keywords:||Maneuvering target tracking|
Markov chain Monte Carlo
|Citation:||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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Nov 14, 2018
WEB OF SCIENCETM
checked on Nov 6, 2018
checked on Nov 17, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.