论文信息 - Fuzzy adaptive Kalman filtering for INS/GPS data fusion

Fuzzy adaptive Kalman filtering for INS/GPS data fusion

This paper is an attempt to generalize the results obtained earlier and presents the method of sensor fusion based on the Adaptive Fuzzy Kalman Filtering. This method has been applied to fuse position signals from the Global Positioning System (GPS) and Inertial Navigation System (INS) for the autonomous mobile vehicles. The presented method has been validated in 3-D environment and is of particular importance for guidance, navigation, and control of jlying vehicles. The Extended Kalman Filter (EKF) and the noise characteristic has been modtjied using the Fuzzy Logic Adaptive System and compared with the performance of regular EKF. This paper discusses extensively the GPS and INS measurement covariance and their influence on Kalman Filter perjormance. It has been demonstrated that the Fuzzy Adaptive Kalman Filter gives better results (more accurate) than the EKF.

Q. Wang | J. Sasiadek

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