Concerning the problems in the process of the spacecraft’s autonomous navigation, the square-root Unscented Kalman Filter(SRUKF) is designed to estimate the relative state between the pursuing spacecraft and the target. C-W equation is discreted to iterate. For the case that all the measuring datas get from radars, the observing equation was deduced. Compared with the conventional extended Kalman Filter(EKF), no Jacobian matrix is required to calculate in this algorithm, the computational cost is reduced and the estimation accuracy is also improved. Simulation results show that the algorithm can quickly converge even for large initial errors and is efficient.


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    Titel :

    The square root Unscented Kalman Filter in spacecrafts autonomous navigation


    Beteiligte:
    Peng Li, (Autor:in) / Shenmin Song, (Autor:in) / Duan, G.R. (Autor:in)


    Erscheinungsdatum :

    2008-12-01


    Format / Umfang :

    516473 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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