›› 2013, Vol. 33 ›› Issue (2): 67-71.doi: 10.3780/j.issn.1000-758X.2013.02.011

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Satellite Attitude Determination Based on the Adaptive Federated Kalman Filter

LI  Peng1, TANG  Jian1, DUAN  Guang-Ren2, SONG  Shen-Min2   

  1. (1 Key Laboratory of Intelligent Computing & Information Processing, Ministry of Education, College of Information and Technology, Xiangtan University,Xiangtan 411105)(2 School of Astronautics, Harbin Institute of Technology, Harbin 150001)
  • Received:2012-04-14 Revised:2012-10-23 Online:2013-04-25 Published:2013-04-25

Abstract: Standard Kalman filter adopts constant covariance of measurement noise. When statistical characteristics of measurement noise changes, estimation error increases, which results in filtering divergence. An adaptive federated Kalman filter was proposed with fuzzy adaptive Kalman filter but not Kalman filter in the subsystem of federated Kalman filter, and the weighted coefficient of covariance matrix was adjusted by fuzzy inference algorithm real-timely. It made the measurement noise of the dynamic equation close to the truth level. When it is applied to multi-sensor attitude determination systems, simulation results demonstrate the true effectiveness of the proposed algorithm.

Key words: Self-adaptive Kalman filter, Federated Kalman filter, Multi-sensor system, Attitude determination, Satellite