Improved design of proposal distribution for particle filter
LIU Zhen-tao1, CAO Bei2, SHEN Xu-bang1
(1. School of Microelectronics, Xidian University, Xi′an 710071, China; 2. Xi′an Institute of Optics and Precision Mechanics of CAS, Xi′an 710119, China);1.School of Microelectronics, Xidian University, Xi′an 710071, China;2.Xi′an Institute of Optics and Precision Mechanics of CAS, Xi′an 710119, 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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Improved design of proposal distribution for particle filter
本站小编 哈尔滨工业大学/2019-10-23
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