Highlights Central difference predictive filter is proposed for satellite attitude determination. The proposed filter has higher estimation accuracy than the traditional PF. The proposed CDPF is more effective and robust than the UKF and traditional PF.

    Abstract Attitude determination is one of the key technologies for Attitude Determination and Control System (ADCS) of a satellite. However, serious model errors may exist which will affect the estimation accuracy of ACDS, especially for a small satellite with low precision sensors. In this paper, a central difference predictive filter (CDPF) is proposed for attitude determination of small satellites with model errors and low precision sensors. The new filter is proposed by introducing the Stirling’s polynomial interpolation formula to extend the traditional predictive filter (PF). It is shown that the proposed filter has higher accuracy for the estimation of system states than the traditional PF. It is known that the unscented Kalman filter (UKF) has also been used in the ADCS of small satellites with low precision sensors. In order to evaluate the performance of the proposed filter, the UKF is also employed to compare it with the CDPF. Numerical simulations show that the proposed CDPF is more effective and robust in dealing with model errors and low precision sensors compared with the UKF or traditional PF.


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    Title :

    Central difference predictive filter for attitude determination with low precision sensors and model errors


    Contributors:
    Cao, Lu (author) / Chen, Xiaoqian (author) / Misra, Arun K. (author)

    Published in:

    Advances in Space Research ; 54 , 11 ; 2336-2348


    Publication date :

    2014-08-19


    Size :

    13 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English