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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:LIU Zhen-tao,CAO Bei,SHEN Xu-bang.Improved design of proposal distribution for particle filter[J].Journal of Harbin Institute Of Technology(New Series),2012,19(6):72-78.DOI:10.11916/j.issn.1005-9113.2012.06.013.
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Improved design of proposal distribution for particle filter
Author NameAffiliation
LIU Zhen-tao School of Microelectronics, Xidian University, Xi′an 710071, China 
CAO Bei Xi′an Institute of Optics and Precision Mechanics of CAS, Xi′an 710119, China 
SHEN Xu-bang School of Microelectronics, Xidian University, Xi′an 710071, China 
Abstract:
One crucial issue in particle filtering is the selection of proposal distribution. Good proposal can effectively alleviate particle degeneracy and thus improve filtering accuracy. In this paper, we propose a new type of proposal distribution for particle filter, called as R-IEKF proposal. By combining iterated extended kalman filter with Rauch-Tung-Striebel optimal smoother, the new proposal integrates the latest observation into system and approximates the true posterior distribution reasonably well, hence generating more precise and stable particles against measurement noise. The simulation results indicate that the improved particle filter with R-IEKF proposal prevails over PF-EKF and UPF both in tracking accuracy and filtering stability. Consequently, PF-RIEKF is a competitive choice in noisy measurement environment.
Key words:  particle filter  proposal distribution  IEKF  Rauch-Tung-Striebel (RTS) smoother
DOI：10.11916/j.issn.1005-9113.2012.06.013
Clc Number:TP391
Fund:

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