GNSS/INS integrated navigation system is particularly outstanding in providing reliable navigation information for land vehicle applications. However, GNSS measurements are easily disturbed in harsh operating environments, especially the accuracy of integrated navigation system integrated with inertial navigation system will be affected accordingly. Hence, a robust adaptive extended Kalman filter procedure is crucial to maintain the stability and reliability of the system. In this study, a robust factor based on local test of standardized residual vector was proposed to deal with potential gross errors, and an adaptive factor based on position dilution of precision which reflect the satellite geometry was proposed to adjust covariance matrix. The robust adaptive factor function models are established to adjust the dynamic model and abnormal measurements. The test results show that the standard extended Kalman filter cannot always give an optimal solution due to the influence of GNSS measurements and satellite geometry especially in the complex environment, while the proposed method improves the reliability of the integrated navigation system by adopting robust adaptive factor.


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    Title :

    GNSS/INS Tightly Coupled Navigation with Robust Adaptive Extended Kalman Filter


    Additional title:

    Int.J Automot. Technol.


    Contributors:
    Wu, Youlong (author) / Chen, Shuai (author) / Yin, Tingting (author)

    Published in:

    Publication date :

    2022-12-01


    Size :

    11 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English







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