Strong Tracking Unscented Kalman Filtering Algorithm Based-on Satellite Attitude Determination System

نویسندگان

  • Min Li
  • Song-yan Wang
  • Ying-chun Zhang
چکیده

Combined with strong tracking filter (STF) theory, the Strong Tracking Square-Root Unscented Kalman Filter (UKF)-based satellite attitude determination algorithm is proposed in this paper. QR decomposition and Cholesyk decomposition are introduced in this paper, which improves the stability of filter. In addition, by introduced adaptive fading factor, the prediction error covariance matrix can be adjusted, thus it can guarantee the strong tracking performance of the proposed algorithm. At last, simulation results show that strong tracking square-root UKF has better stability, robustness and mutation status tracking capability than Square-Root UKF and Strong Tracking UKF.

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تاریخ انتشار 2014