DocumentCode
2744226
Title
Adaptive Avoiding Divergence Algorithm for GPS/DR Integration Based on Fuzzy Logic
Author
Zheng, Guixing ; Zhao, Rui ; Guo, Qiang ; Liu, Luyuan ; Bai, Lina ; Du, Lei
Author_Institution
Dept. of Autom., Tsinghua Univ., Beijing
Volume
2
fYear
0
fDate
0-0 0
Firstpage
8679
Lastpage
8682
Abstract
In order to solve the divergence which is likely to emergence in Kalman filter applied in GPS/DR vehicle integration, the adaptive algorithm based on fuzzy logic to avoid filter divergence is designed which rely on the convergence criterion of Kalman filter, and simulation experimentations are carried through. The Matlab simulations manifested that the location precision and the tracking capability are improved by the algorithm and the divergence is prevented
Keywords
Global Positioning System; Kalman filters; adaptive control; fuzzy control; road vehicles; GPS-dead reckoning vehicle integration; Kalman filter; Matlab simulation; adaptive avoiding divergence algorithm; fuzzy logic; Adaptive algorithm; Convergence; Covariance matrix; Design automation; Filters; Fuzzy logic; Global Positioning System; Mathematical model; Technological innovation; Vehicles; Avoiding divergence; Fuzzy; GPS/DR; Kalman;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location
Dalian
Print_ISBN
1-4244-0332-4
Type
conf
DOI
10.1109/WCICA.2006.1713675
Filename
1713675
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