HighlightsThe novel DGKF is proposed based on the previous and current time-step’s measurement residuals.The robust design and UT strategy are used to improve the DGKF to obtain the RDG-UKF method.Simulation results show that the proposed RDG-UKF has the advantages than the traditional UKF.

    AbstractLimited by the low precision of small satellite sensors, the estimation theories with high performance remains the most popular research topic for the attitude estimation. The Kalman filter (KF) and its extensions have been widely applied in the satellite attitude estimation and achieved plenty of achievements. However, most of the existing methods just take use of the current time-step’s priori measurement residuals to complete the measurement update and state estimation, which always ignores the extraction and utilization of the previous time-step’s posteriori measurement residuals. In addition, the uncertainty model errors always exist in the attitude dynamic system, which also put forward the higher performance requirements for the classical KF in attitude estimation problem. Therefore, the novel robust double gain unscented Kalman filter (RDG-UKF) is presented in this paper to satisfy the above requirements for the small satellite attitude estimation with the low precision sensors. It is assumed that the system state estimation errors can be exhibited in the measurement residual; therefore, the new method is to derive the second Kalman gain K k 2 for making full use of the previous time-step’s measurement residual to improve the utilization efficiency of the measurement data. Moreover, the sequence orthogonal principle and unscented transform (UT) strategy are introduced to robust and enhance the performance of the novel Kalman Filter in order to reduce the influence of existing uncertainty model errors. Numerical simulations show that the proposed RDG-UKF is more effective and robustness in dealing with the model errors and low precision sensors for the attitude estimation of small satellite by comparing with the classical unscented Kalman Filter (UKF).


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    Title :

    Robust double gain unscented Kalman filter for small satellite attitude estimation


    Contributors:
    Cao, Lu (author) / Yang, Weiwei (author) / Li, Hengnian (author) / Zhang, Zhidong (author) / Shi, Jianjun (author)

    Published in:

    Advances in Space Research ; 60 , 3 ; 499-512


    Publication date :

    2017-03-10


    Size :

    14 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    Residual Based Adaptive Unscented Kalman Filter for Satellite Attitude Estimation

    Soken, H. / Sakai, S.-i. / American Institute of Aeronautics and Astronautics | British Library Conference Proceedings | 2012