Fuzzy adaptive Kalman filter for marine INS/GPS navigation

The integrated INS/GPS navigation system, which is applied to the marine, is necessary to provide long-term high accurate navigation information. A fuzzy adaptive Kalman filter (FAKF) is developed to estimate the navigational information accurately, and achieve the in-flight alignment and positioning. The proposed algorithm adaptively changes the corresponding weighted factor via fuzzy logic for every observable, and utilizes the weighted matrixes to adjust the Kalman filter. The weighted-matrixes come from four channels, which respectively respond to the residuals of latitude, longitude, east velocity and north velocity, in the fuzzy logic controller. The result of simulation and test shows perfect knowledge of the a prior information will be only of secondary importance when the estimator selects the FAKF to achieve integrated navigation, not conventional Kalman filter (CKF). In the case of insufficiently known a prior statistics, the in-flight alignment and positioning performance of FAKF is better than CKF, and FAKF is more efficient.