Adaptive robust filtering algorithm in GPS/DR integrated navigation

In view that the mathematical model based on GPS /DR vehicle integrated system is non-linear,and using EKF(extended Kalman filter)to make linearization could cause significant errors in its filtering results,the paper introduces an adaptive robust filter.The simulative computation of the adaptive robust filtering and adaptive Kalman filtering are studied respectively,and the results show that the robust adaptive filtering can adaptively determine the covariance matrix of observation noise,and can adaptively regulate the covariance matrix of state parameter noise by adaptive factor.This method can control the impacts of observed noise abnormal and dynamic model noise abnormal on the estimation of state parameters,and make the state estimation more reasonable.The experimental result shows that the adaptive robust filtering algorithm reduces the position error to 30 m;while the position error by the adaptive Kalman filtering algorithm reduces it to 18 m,and its error control is more stable.