DocumentCode :
2544001
Title :
A New Mixed Particle Filter Based on an Auxiliary Model
Author :
Luo, YinFeng ; Yu, Shenglin
Author_Institution :
Coll. of Autom. Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
fYear :
2009
fDate :
4-6 Nov. 2009
Firstpage :
1
Lastpage :
5
Abstract :
Particle filter is an effective method for non-linear filter and it has been gained special attention of researchers in various fields. There will be a new mixed particle filter (PUPF) proposed in this paper based on the general particle filter and the unscented particle filter. lt first uses the general particle filter to generate particles for estimating the state at time k and then a new auxiliary model will be introduced. We would use the unscented particle filter to estimate the state at time k the second time. This structure makes use of the latest observation information, it has small error and better stability. The experimental results indicate that the proposed particle filter´s performance outperforms the other four particle filters .The result indicates that the PUPF is a useful method for nonlinear filter problems.
Keywords :
nonlinear filters; particle filtering (numerical methods); auxiliary model; mixed particle filter; nonlinear filter; unscented particle filter; Automation; Educational institutions; Nonlinear filters; Particle filters; Stability; State estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2009. CCPR 2009. Chinese Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4199-0
Type :
conf
DOI :
10.1109/CCPR.2009.5344151
Filename :
5344151
Link To Document :
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