Highlights A federated NPF for the gyroless attitude determination system with star sensor and GPS sensor is presented. This approach combines the good qualities of both the NPF and federated filter. A fault detection and isolation algorithm is applied to the proposed federated NPF.

    Abstract This paper presents a federated nonlinear predictive filter (NPF) for the gyroless attitude determination system with star sensor and Global Positioning System (GPS) sensor. This approach combines the good qualities of both the NPF and federated filter. In order to combine them, the equivalence relationship between the NPF and classical Kalman filter (KF) is demonstrated from algorithm structure and estimation criterion. The main features of this approach include a nonlinear predictive filtering algorithm to estimate uncertain model errors and determine the spacecraft attitude by using attitude kinematics and dynamics, and a federated filtering algorithm to process measurement data from multiple attitude sensors. Moreover, a fault detection and isolation algorithm is applied to the proposed federated NPF to improve the estimation accuracy even when one sensor fails. Numerical examples are given to verify the navigation performance and fault-tolerant performance of the proposed federated nonlinear predictive attitude determination algorithm.


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    Title :

    Federated nonlinear predictive filtering for the gyroless attitude determination system


    Contributors:
    Zhang, Lijun (author) / Qian, Shan (author) / Zhang, Shifeng (author) / Cai, Hong (author)

    Published in:

    Advances in Space Research ; 58 , 9 ; 1671-1681


    Publication date :

    2016-07-15


    Size :

    11 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






    Gyroless Attitude Estimation for Hipparcos

    Val Serra, S. / Carron, C. / Heger, D. et al. | British Library Conference Proceedings | 1994