Fuzzy adaptive Kalman filtering for INS/GPS data fusion

Author

Sasiadek, J.Z. ; Wang, Q. ; Zeremba, M.B.

Author_Institution

Dept. of Mech. & Aerosp. Eng., Carleton Univ., Ottawa, Ont., Canada

fYear

2000

fDate

2000

Firstpage

181

Lastpage

186

Abstract

Presents a method for sensor fusion based on adaptive fuzzy Kalman filtering. The method is applied in fusing position signals from Global Positioning Systems (GPS) and inertial navigation systems (INS) for autonomous mobile vehicles. The presented method has been validated in a 3-D environment and is of particular importance for guidance, navigation, and control of flying vehicles. The extended Kalman filter (EKF) and the noise characteristics are modified using the fuzzy logic adaptive system, and compared with the performance of a regular EKF. It is demonstrated that the fuzzy adaptive Kalman filter gives better results, in terms of accuracy, than the EKF

Keywords

Global Positioning System; adaptive Kalman filters; fuzzy control; inertial navigation; mobile robots; nonlinear filters; sensor fusion; INS/GPS data fusion; autonomous mobile vehicles; extended Kalman filter; flying vehicles; fuzzy adaptive Kalman filtering; position signals; Adaptive filters; Filtering; Fuzzy logic; Global Positioning System; Inertial navigation; Kalman filters; Mobile robots; Remotely operated vehicles; Sensor fusion; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control, 2000. Proceedings of the 2000 IEEE International Symposium on

Conference_Location

Rio Patras

ISSN

2158-9860

Print_ISBN

0-7803-6491-0

Type

conf

DOI

10.1109/ISIC.2000.882920

Filename

882920