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[1] Zhang Weiming, Zhang Yanhua, Zhong Shan, Du Gang, et al. New approach of Kalman filter to nonlinear system [J]. Journal of Southeast University (English Edition), 2005, 21 (1): 24-28. [doi:10.3969/j.issn.1003-7985.2005.01.006]
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New approach of Kalman filter to nonlinear system()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
21
Issue:
2005 1
Page:
24-28
Research Field:
Electronic Science and Engineering
Publishing date:
2005-03-30

Info

Title:
New approach of Kalman filter to nonlinear system
Author(s):
Zhang Weiming1 Zhang Yanhua1 Zhong Shan2 Du Gang1
1Department of Information Measurement Technology and Instruments, Shanghai Jiaotong University, Shanghai 200030, China
2The Second Academy, China Aerospace Science and Industry Corporation, Beijing 100854, China
Keywords:
nonlinear extended Kalman filter unscented Kalman filter unscented transformation
PACS:
TN713
DOI:
10.3969/j.issn.1003-7985.2005.01.006
Abstract:
In order to achieve higher accuracy in nonlinear/non-Gaussian state estimation, this paper proposes a new unscented Kalman filter(UKF).It uses a deterministic sampling approach.We choose the unscented transformation(UT)scaling parameters α=0.85, β=2, l=0 to construct 2n+1 sigma points.These sigma points completely capture the mean and covariance of the Gaussian random variables of the nonlinear system Yi=F(Xi).Simulation results show that the posterior mean and covariance of the sigma points can achieve the accuracy of the third-order Taylor series expansion after having propagated through the true nonlinear system Yi=F(Xi).Extended Kalman filter(EKF)only can achieve the first-order accuracy.The computational complexity of UKF is the same level as that of EKF.UKF can yield better performance and higher accuracy than EKF.

References:

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Memo

Memo:
Biographies: Zhang Weiming(1969—), male, graduate;Zhang Yanhua(corresponding author), male, professor, zhangyh@sjtu.edu.cn.
Last Update: 2005-03-20