DocumentCode :
3539426
Title :
A novel cubature Kalman filter for nonlinear state estimation
Author :
Xin-Chun Zhang
Author_Institution :
Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear :
2013
fDate :
10-13 Dec. 2013
Firstpage :
7797
Lastpage :
7802
Abstract :
The cubature Kalman filter (CKF) is more preferred over the unscented Kalman filter (UKF) for its more stable performance. The CKF employs a third-degree spherical-radial cubature rule to numerically compute the integrals encountered in nonlinear filtering problems. The third-degree cubature rule-based filter, however, is not accurate enough in many real-life applications. Moreover, the spherical cubature formula that has been used to develop the CKF has some drawbacks in computation, most notably its inconvenient properties in high-dimensional state estimation problems. To tackle these problems, a new approach to nonlinear state estimation using only an embedded cubature rule, which we have named the square-root embedded cubature Kalman filter (SECKF) is proposed in this work. The experimental results, presented herein, demonstrate the superior performance of the SECKF over conventional nonlinear filters.
Keywords :
Kalman filters; nonlinear filters; state estimation; SECKF; UKF; cubature rule-based filter; embedded cubature rule; high-dimensional state estimation problems; nonlinear filtering problems; nonlinear state estimation; spherical cubature formula; spherical-radial cubature rule; square-root embedded cubature Kalman filter; unscented Kalman filter; Filtering theory; Kalman filters; Noise measurement; Nonlinear filters; State estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
ISSN :
0743-1546
Print_ISBN :
978-1-4673-5714-2
Type :
conf
DOI :
10.1109/CDC.2013.6761127
Filename :
6761127
Link To Document :
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