DocumentCode :
2084602
Title :
An Improved Unscented Kalman Filter Based on STF for Nonlinear Systems
Author :
Li, Zheng ; Pan, Pingjun ; Gao, Dongfeng ; Zhao, Dayong
Author_Institution :
Commun. Navig. & Comm & Autom. Instn., Equip. Acad. of Airforce, Beijing, China
fYear :
2009
fDate :
17-19 Oct. 2009
Firstpage :
1
Lastpage :
5
Abstract :
The advantages of recently developed Unscented Kalman Filter (UKF) for nonlinear systems are significant with its ease to implement, better accuracy and same order of computational complexity. However, UKF has as bad robustness as extended Kalman filter (EKF) on the modelling uncertainty, and is sensitive to the initial conditions. To overcome the limitations of UKF, an improved UKF based on the theory of strong tracking filters (STF) is developed in the paper. The improved filter could adjust a filtering gain matrix on line by introducing a time-varied fading matrix. Its effectiveness is demonstrated using a simulation example of target tracking. The simulation results show that the improved UKF has good robustness and can rapidly converge.
Keywords :
Kalman filters; nonlinear filters; tracking filters; extended Kalman filter; nonlinear system; strong tracking filter; unscented Kalman filter; Additive noise; Automation; Filtering theory; Filters; Navigation; Nonlinear systems; Robustness; Target tracking; Uncertainty; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4129-7
Electronic_ISBN :
978-1-4244-4131-0
Type :
conf
DOI :
10.1109/CISP.2009.5301464
Filename :
5301464
Link To Document :
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