| 基于强跟踪UKF的航天器自主导航间接量测滤波算法 |
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| 引用本文： | 杨文博,李少远. 基于强跟踪UKF的航天器自主导航间接量测滤波算法[J]. 系统工程与电子技术, 2011, 33(11): 2485-2491. DOI: 10.3969/j.issn.1001-506X.2011.11.27 |
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| 作者姓名： | 杨文博 李少远 |
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| 作者单位： | 上海交通大学自动化系系统控制与信息处理教育部重点实验室, 上海 200240 |
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| 基金项目： | 国家自然科学基金(60825302)资助课题 |
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| 摘 要： | 针对广义卡尔曼滤波(extended Kalman filter, EKF)和无迹卡尔曼滤波(unscented Kalman filter, UKF)缺乏对系统异常的在线自适应调整能力、导致滤波器精度降低的问题,提出了一种将强跟踪滤波(strong tracking filter, STF)和UKF相结合的滤波算法,并进一步采用部分状态信息作为间接观测量,同时量测噪声方差阵实时调整,从而避免了对观测方程求取Jacobi矩阵的过程,使滤波器的设计得到简化。将该算法应用于航天器自主导航系统中,仿真结果表明,该算法在系统出现突变或缓变异常时,能够迅速检测出异常,在保证较高估计精度的同时,提高了系统的可靠性。
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| 关 键 词： | 自主导航 强跟踪滤波 无迹卡尔曼滤波 间接量测 |
Autonomous navigation filtering algorithm for spacecraft based on strong tracking UKF |
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| YANG Wen-bo,LI Shao-yuan. Autonomous navigation filtering algorithm for spacecraft based on strong tracking UKF[J]. System Engineering and Electronics, 2011, 33(11): 2485-2491. DOI: 10.3969/j.issn.1001-506X.2011.11.27 |
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| Authors: | YANG Wen-bo LI Shao-yuan |
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| Affiliation: | Key Laboratory of System Control and Information Processing (Ministry of Education) Department of Automation, Shanghai Jiaotong University, Shanghai 200240, China |
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| Abstract: | An improved filter algorithm combined strong tracking filter(STF) with unscented Kalman filter(UKF) is proposed to enhance poor performance of extended Kalman filter(EKF) and UKF in online adaptive adjustment ability and estimation accuracy when systems are abnormal.The process of solving Jacobi matrix in observer equation is avoided by deeming partial state information as indirect measurement and adjusting the measurement noise variance matrix online,which makes the filter design more simplified.The algori... |
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| Keywords: | autonomous navigation strong tracking filter(STF) unscented Kalman filter(UKF) indirect measurement |
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