DocumentCode
420800
Title
Nonlinear target tracking based on particle filter
Author
Deng, Xiaolong ; Xie, Jianying
Author_Institution
Dept. of Autom., Shanghai Jiao Tong Univ., China
Volume
2
fYear
2004
fDate
15-19 June 2004
Firstpage
1618
Abstract
For the reason of being able to deal with any nonlinear or non-Gaussian distributions, particle filters have been favored by many researchers and been widely applied in many fields. Based on the particle filter, the modified extended Kalman filter (EKF) proposed function, the suitable resampling algorithm, the rejection sampling and etc. are introduced in nonlinear target tracking. And the simulation results confirm that the improved particle filter outperforms the basic one.
Keywords
Bayes methods; Kalman filters; filtering theory; signal sampling; target tracking; modified extended Kalman filter; nonlinear Bayesian problem; nonlinear target tracking; particle filter; rejection sampling; resampling algorithm; Automation; Bayesian methods; Density functional theory; Filtering; Noise measurement; Nonlinear equations; Particle filters; Proposals; Recursive estimation; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN
0-7803-8273-0
Type
conf
DOI
10.1109/WCICA.2004.1340926
Filename
1340926
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