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Inventi Impact - Aerospace Engineering

Articles

  • Inventi:eae/61/14
    AN EFFICIENT NONLINEAR FILTER FOR SPACECRAFT ATTITUDE ESTIMATION
    Bing Liu, Zhen Chen, Xiangdong Liu, Fan Yang

    Increasing the computational efficiency of attitude estimation is a critical problem related to modern spacecraft, especially for those with limited computing resources. In this paper, a computationally efficient nonlinear attitude estimation strategy based on the vector observations is proposed.The Rodrigues parameter is chosen as the local error attitude parameter, to maintain the normalization constraint for the quaternion in the global estimator. The proposed attitude estimator is performed in four stages. First, the local attitude estimation error system is described by a polytopic linear model. Then the local error attitude estimator is designed with constant coefficients based on the robust H2 filtering algorithm. Subsequently, the attitude predictions and the local error attitude estimations are calculated by a gyro based model and the local error attitude estimator. Finally, the attitude estimations are updated by the predicted attitude with the local error attitude estimations. Since the local error attitude estimator is with constant coefficients, it does not need to calculate thematrix inversion for the filter gain matrix or update the Jacobianmatrixes online to obtain the local error attitude estimations. As a result, the computational complexity of the proposed attitude estimator reduces significantly. Simulation results demonstrate the efficiency of the proposed attitude estimation strategy.

    How to Cite this Article
    CC Compliant Citation: Bing Liu, Zhen Chen, Xiangdong Liu, and Fan Yang, “An Efficient Nonlinear Filter for Spacecraft Attitude Estimation,” International Journal of Aerospace Engineering, vol. 2014, Article ID 540235, 11 pages, 2014. doi:10.1155/2014/540235. Copyright © 2014 Bing Liu et al. This is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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