Fuzzy adaptive Kalman filtering for INS/GPS data fusion

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