According to Kalman filtering for strapdown inertial navigation based integrated navigation, the measurement often has interference. The interference can reduce the effect of filtering estimation. In this paper, a robust sequential Kalman filtering algorithm based on Huber is proposed. The algorithm combines sequential Kalman and Huber. In numerical experiments, the estimation of the robust sequential Kalman filter and the Kalman filter are compared under the presence of pollution in the measurement. The results show that the robust sequential Kalman filtering algorithm has strong anti-interference capability.


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    Title :

    Robust sequential Kalman filter for inertial integrated


    Contributors:
    Xin, Lu (author) / Bai-qing, Hu (author) / Guang-jun, Zhang (author) / Bo-yang, Xue (author)


    Publication date :

    2018-08-01


    Size :

    466882 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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