Adaptive Fuzzy Control Algorithm for an Integrated Navigation of SINS and the Odometer

Accuracy is one of the most important requirements for land vehicle navigation. Since the accuracy of SINS degrades rapidly with time while that of odometer degrades with distance, a SINS/OD integrated navigation system based on Kalman filter is adopted to improve positioning precision by making full use of the advantages of both methods. The measurement result of the odometer is greatly influenced by the road condition, and sometimes the output value is even wrong. Therefore, a novel adaptive fuzzy control algorithm is put forward to improve the robustness and accuracy of the navigation system. The in-out subjection factor functions are set up based on the innovation information of the filter and the velocity ratio between the values measured by SINS and the odometer; the velocity gain of the odometer can be adaptively changed based on the selected fuzzy control rules. Simulation results show that the proposed algorithm can increase the navigation precision by adaptively correcting the measurement error of the odometer.