Research on port vehicle combined positioning method based on fuzzy Kalman filter

Aiming at the problems of BDS/INS integrated navigation system positioning failure in the obstructed environment, by analyzing the impact of sensor status changes in the integrated navigation system on positioning accuracy, we design a fuzzy logic inference system based on the status of the system, combined with the Kalman filter algorithm, the positioning accuracy is improved by real-time adjustment of the noise variance of the system measurement. Finally, experiments were carried out on unmanned vehicles in a port environment. Experiment shows that the proposed method can effectively improve the positioning accuracy of unmanned vehicles in an occluded environment, and has good robustness.