DocumentCode
2759852
Title
PF-UKF-RJMCMC Approaches for Radar Target-Tracking
Author
Huibo, Zhao ; Quan, Pan
Author_Institution
Coll. of Autom., Northwestern Polytech. Univ., Xi´´an, China
Volume
2
fYear
2009
fDate
25-26 July 2009
Firstpage
373
Lastpage
376
Abstract
Nonlinear problem of maneuvering target is a hot and difficult topic in radar target tracking fielding. This paper outline the the pros and cons of non-linear filtering methods nowdays, emphatically analyses uncertainty sampling and random sampling method, describe Markov chain Monte Carlo algorithms, along with Reversible Jump ratio improving methods. and try to present a comprehensive picture of the performance comparison among classical tracking methods combining RJMCMC, including PF, EKF-PF, UKF-PF techniques from the varied literature that have seen wide application in radar target tracking field. Simulations on maneuvering target radar tracking are carried out to validate the performance of the proposed scheme in comparison with existing methods.
Keywords
Kalman filters; Markov processes; Monte Carlo methods; nonlinear filters; particle filtering (numerical methods); radar tracking; random processes; target tracking; Markov chain Monte Carlo algorithm; nonlinear filtering method; particle filter; radar target-tracking; random sampling; reversible jump MCMC; reversible jump ratio; target maneuvering; uncertainty sampling; unscented Kalman filter; Automation; Educational institutions; Filtering; Kalman filters; Particle filters; Radar tracking; Sampling methods; Space technology; Target tracking; Uncertainty; RJMCMC; UPF; nonlinear; target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Computer Science, 2009. ITCS 2009. International Conference on
Conference_Location
Kiev
Print_ISBN
978-0-7695-3688-0
Type
conf
DOI
10.1109/ITCS.2009.214
Filename
5190257
Link To Document