As it is difficult to get an accurate mathematical noise model under various dynamic interference conditions, Strap-down Inertial Navigation System (SINS) was difficult to realize self-alignment. Although the fuzzy adaptive Kalman filter can be used to realize the SINS self-alignment, the algorithm complexity is high and the error term is unstable. To solve this problem, a novel self-alignment method using real-time adaptive filter was developed in this paper. This method is based on the theory of fuzzy adaptive adjustment and used the filter stability as the criterion. The exponential function was used to replace the fuzzy inference calculation, which eliminated the complex process of fuzzy, fuzzy inference and de-fuzzy. The stability and accuracy of the adaptive filter was also improved. Finally, the simulation process was used to test the algorithm of this method, and the results demonstrated that the self-alignment using real-time adaptive filter method reduced the complexity of the algorithm and had better stability and alignment accuracy.


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    Titel :

    Self-alignment for strapdown INS using real-time adaptive filter


    Beteiligte:
    Zhao, Jian (Autor:in) / Pei, Fu-jun (Autor:in) / Liu, Hong-yun (Autor:in)


    Erscheinungsdatum :

    2016-08-01


    Format / Umfang :

    99257 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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