A New Attitude Determination Algorithm Based on Fuzzy Adaptive Kalman Filter
- Paper number
IAC-08.C1.7.11
- Author
Dr. Du Yaling, China Academy of Launch Vehicle Technology, China
- Coauthor
Mr. Liu Jizhong, Beijing Aerospace Automatic Control Institute, China
- Coauthor
Mr. Gao Xiaojing, Beijing Aerospace Automatic Control Institute, China
- Year
2008
- Abstract
Attitude determination is important for mostly space missions. How to make full use of Inertial Measurement Unit (IMU) information in attitude determination is studied in this paper for system high accuracy and independence. The new attitude determination algorithm based on the fuzzy adaptive Kalman filter is presented. The filter uses integrated values from the angular rate information measured by gyros and estimated roll and pitch angles produced by the accelerometers. According to the system acceleration affected the precision of filter directly, the fuzzy logic controller is designed with 9 rules. The state equation and the measure equation of Kalman filter are described in detail. The noise covariance is modified real time by the fuzzy logic adaptive controller in order to be optimal and improve attitude accuracy. The theory analysis proves the fuzzy adaptive Kalman filter is converged and can compensate attitude drift when the system acceleration is small. Simulation and experimental results show that the new attitude determination algorithm can improve the system attitude precision effectively.
- Abstract document
- Manuscript document
IAC-08.C1.7.11.pdf (🔒 authorized access only).
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