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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.10 P.1717~1722

http://doi.org/10.1631/jzus.2006.A1717


A filter algorithm for multi-measurement nonlinear system with parameter perturbation


Author(s):  GUO Yun-fei, WEI Wei, XUE An-ke, MAO Dong-cai

Affiliation(s):  School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   zizhe_yjys@yahoo.com.cn

Key Words:  IMM-PF, Parameter perturbation, Multi-measurement


GUO Yun-fei, WEI Wei, XUE An-ke, MAO Dong-cai. A filter algorithm for multi-measurement nonlinear system with parameter perturbation[J]. Journal of Zhejiang University Science A, 2006, 7(10): 1717~1722.

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author="GUO Yun-fei, WEI Wei, XUE An-ke, MAO Dong-cai",
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pages="1717~1722",
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publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A1717"
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%J Journal of Zhejiang University SCIENCE A
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T1 - A filter algorithm for multi-measurement nonlinear system with parameter perturbation
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2006.A1717


Abstract: 
An improved interacting multiple models particle filter (IMM-PF) algorithm is proposed for multi-measurement nonlinear system with parameter perturbation. It divides the perturbation region into sub-regions and assigns each of them a particle filter. Hence the perturbation problem is converted into a multi-model filters problem. It combines the multiple measurements into a fusion value according to their likelihood function. In the simulation study, we compared it with the IMM-KF and the H-infinite filter; the results testify to its advantage over the other two methods.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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[9] Tsaknakis, H., Athans, M., 1994. Tracking maneuvering targets using H filters. ACC, 2:1796-1803.

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