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Attitude determination for satellite using adaptive unscented Kalman filter
L. Xiao; S.-J. Wang; L. Chang and M.-L. Zhou
2021
发表期刊Guangxue Jingmi Gongcheng/Optics and Precision Engineering
ISSN1004924X
卷号29期号:3页码:637-645
摘要Poor stability and low tracking accuracy are significant issues in existing algorithms for satellite attitude determination. An adaptive unscented Kalman filter (AUKF) algorithm was proposed to overcome these issues and estimate the three-axis attitude of satellite by modeling error and external disturbance. First, the working principle of attitude determination based on gyro sensor was analyzed, following which the satellite attitude kinematics equation, with error quaternion as state variable, was derived. An adaptive matrix was introduced to adjust the measurement noise covariance matrix. Based on the filtering divergence criterion, the system noise covariance matrix was adaptively modified to suppress potential divergence in the filtering process, and a good adaptive performance was obtained. Finally, it is demonstrated through experimental verification that, compared with robust AUKF algorithm, the accuracy of three-axis estimation (RMSE) of AUKF improves by 30.0%, 34.1%, and 22.4%, respectively, when the parameter estimation is not accurate. Thus, the algorithm meets the requirements of high precision and strong robustness for satellite attitude determination. 2021, Science Press. All right reserved.
DOI10.37188/OPE.20212903.0637
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收录类别EI
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文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/65066
专题中国科学院长春光学精密机械与物理研究所
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L. Xiao,S.-J. Wang,L. Chang and M.-L. Zhou. Attitude determination for satellite using adaptive unscented Kalman filter[J]. Guangxue Jingmi Gongcheng/Optics and Precision Engineering,2021,29(3):637-645.
APA L. Xiao,S.-J. Wang,&L. Chang and M.-L. Zhou.(2021).Attitude determination for satellite using adaptive unscented Kalman filter.Guangxue Jingmi Gongcheng/Optics and Precision Engineering,29(3),637-645.
MLA L. Xiao,et al."Attitude determination for satellite using adaptive unscented Kalman filter".Guangxue Jingmi Gongcheng/Optics and Precision Engineering 29.3(2021):637-645.
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