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基于卫星编队的空间碎片视觉高精度导航方法
引用本文:杨博,王浩帆,苗峻,赵晓涛. 基于卫星编队的空间碎片视觉高精度导航方法[J]. 中国空间科学技术, 2019, 39(1): 40. DOI: 10.16708/j.cnki.1000-758X.2018.0073
作者姓名:杨博  王浩帆  苗峻  赵晓涛
作者单位:1北京航空航天大学宇航学院,北京1000832北京控制工程研究所,北京100190
摘    要:视觉方法被广泛应用于空间碎片这类和卫星之间没有任何通信的非合作目标导航。针对观测过程中视觉传感器的像差偏差引起位置不确定的问题,提出了利用卫星编队的立体视觉导航方法。首先,利用卫星编队构造了长基线的视觉传感器,通过Fisher矩阵对系统的可观测性进行了分析,验证了系统是可观的;其次,对视觉传感器进行了误差分析,通过安排最优视差角,使多颗卫星的观测信息融合达到最优;最后,应用卫星编队的视觉导航方法对空间碎片进行了导航仿真验证。结果表明,基于卫星编队的视觉导航方法可以显著减小观测误差,精度能达到01m量级,而且编队构形简单,易于工程实现。

关 键 词:空间碎片  卫星编队  立体视觉  可观测性  高精度导航  

High precision visual navigation for space debris based on satellite formation
YANG Bo,WANG Haofan,MIAO Jun,ZHAO Xiaotao. High precision visual navigation for space debris based on satellite formation[J]. Chinese Space Science and Technology, 2019, 39(1): 40. DOI: 10.16708/j.cnki.1000-758X.2018.0073
Authors:YANG Bo  WANG Haofan  MIAO Jun  ZHAO Xiaotao
Affiliation:1School of Astronautics, Beihang University,Beijing100083, China2Beijing Institute of Control Engineering, Beijing100190, China
Abstract:Visual methods are widely used for non cooperative targets navigation because there is no communication among satellites and non cooperative targets like space debris. To solve the uncertainty positions caused by aberrations of visual sensors, a stereoscopic visual navigation strategy based on satellite formation was formulated. Firstly, a long baseline visual sensor was constructed by satellite formation. The observability of the system was analyzed and verified by Fisher matrix. Secondly, the error analysis of the stereo sensor was performed, and by arranging the optimal parallax angle, the measurement information fusion of multiple satellites was optimized. Finally, the proposed method is applied in the navigation of space debris. The simulation results demonstrate that the satellite navigation based visual navigation can significantly reduce the observation errors, the accuracy can reach the order of 0.1m, and the formation configuration is simple and easy to implement.
Keywords:space debris  satellites  stereo vision  observability  navigation  
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