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Research on robust adaptive Kalman filter for integrated navigation

FU Xinru;SUN Wei;XU Aigong;DING Wei;DUAN Shunli;Liaoning Technical University;  
Aiming at the improvement of the positioning accuracy and stability requirements of integrated navigation system,a Kalman filtering algorithm based on observation noise covariance and robust adaptive is introduced.Using the innovation vector and the moving window covariance analysis,an adaptive factor constructed by the prediction residual vector is proposed by analyzing the problem of the adaptive factor constructed by the statistic of the variance component.Using the innovation vector and the moving window covariance analysis,the observed noise covariance matrix is dynamically modified.By analyzing the problems of adaptive factor constructed by statistical quantity based on state variance and variance component,an adaptive factor constructed by prediction residual vector is proposed.The simulation results show that the proposed method can effectively suppress the influence of observed anomaly on the positioning accuracy of integrated navigation.
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