Aimed at the problem that extended Kalman filter(EKF)will diverge in combined navigation,an fuzzy control-based adaptive Kalman filter algorithm(FAKF)is studied,which calculates the exponential weighting factor through a fuzzy controller to adjust the size of the measurement noise in real time to ensure the filtering accuracy,and effectively suppress the filtering divergence.Aimed at the situation that GPS cannot provide the attitude angle for combined solution,the combination of polarized light and SINS is used for the attitude solution.In this paper,the fuzzy control-based FAKF and EKF algorithms are compared and verified by sim-ulating the GPS/SINS/polarized light combined navigation system,the positional accuracy of the system increases by 56.81％,65.17％,and 45.99％in the east,north,and heading,respectively,the velocity accuracy by 46.99％,54.01％,and 43.82％,and the pitch angle and heading angle by 58.01％and 53.58％,respectively,which proves the advantages of the method.
维普
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