Research on GPS/INS integrated navigation system based on fuzzy adaptive Kalman filtering

This paper presents a novel vehicle GPS/INS integrated navigation algorithm based on Fuzzy Adaptive Kalman Filtering. This method is mainly used in vehicle GPS/INS integrated navigation system to deal with time varied statistic of measurement noise in different working conditions. By monitoring if the ratio between filter residual and actual residual is near 1, this algorithm modifies recursively the measurement noise covariance of Kalman Filtering online using the Fuzzy Inference System (FTS) to make the covariance close to real measurement covariance gradually. Accordingly the Kalman filter performs optimally and the accuracy of the navigation system is improved. Simulations in INS/GPS integrated navigation system demonstrate that the Fuzzy Adaptive Kalman Filtering is adaptive to time varied measurement noise and gives the better results than the regular Kalman Filtering.