DocumentCode :
1822945
Title :
A New Interacting Multiple Model Algorithm Based on the Unscented Particle Filter
Author :
Xiaolong, Deng ; Pingfang, Zhou
Author_Institution :
Dept. of Mech. Eng., Jiangsu Coll. of Inf. Technol., Wuxi, China
Volume :
1
fYear :
2009
fDate :
18-20 Aug. 2009
Firstpage :
419
Lastpage :
422
Abstract :
Combining the interacting multiple model (IMM) and the unscented particle filter (UPF), a new multiple model filtering algorithm is presented. Multiple models can adapt to targets´ high maneuvering. Particle filter can deal with the nonlinear or non-Gaussian problems and the unscented Kalman filter (UKF) may improve the approximate accuracy. Compared with other interacting multiple model algorithms in the target tracking simulations, the results demonstrate the validity of the new filtering method, that is, particle filter with the UKF proposal.
Keywords :
Kalman filters; particle filtering (numerical methods); interacting multiple model algorithm; multiple model filtering algorithm; nonGaussian problem; nonlinear problem; unscented Kalman filter; unscented particle filter; Degradation; Density functional theory; Filtering algorithms; Information security; Mechanical engineering; Particle filters; Predictive models; Proposals; Target tracking; Taylor series; interacting multiple model; particle filter; target tracking; unscented particle filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
Conference_Location :
Xian
Print_ISBN :
978-0-7695-3744-3
Type :
conf
DOI :
10.1109/IAS.2009.214
Filename :
5284137
Link To Document :
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