摘要
为了减小导航星库容量,提出了一种星敏感器导航星筛选算法。将在全天球上生成的均匀分布的光轴随机矢量作为蒙特卡罗实施样本,将每个光轴矢量确定的外接圆视场内的亮星依次作为星子集,将星子集在建星库中没有的星增补进在建星库,并丢弃重复星,遍历所有实施样本后即得到导航星库。仿真条件如下:星敏感器视场为15°×15°,极限星等为5.6 m,星间角距阈值为1°,星图匹配环节所需导航星数为15。此算法构建的导航星库改善了导航星分布的均匀性,在适应星图匹配的充要性意义上,星库中的导航星数达到最少,进而减少了匹配模式库的条数,降低了内存需求,这对星敏感器设计具有工程实用价值。
In order to reduce the capacity of the navigation star database,an algorithm for screening navigation stars on star sensors is proposed. Uniformly distributed optical random vectors on the celestial sphere are generated and used for the Monte Carlo samples. The bright stars in the circumferential field of view(FOV)determined by each optical axis vector are in turn taken as the star subsets. The stars not found in the constructing star database are added to the constructing database in these star subsets and simultaneously the duplicate stars are discarded. After traversing all the implementation samples,one can finally obtain the navigation star database. The simulation condition is set as follows. The FOV of the star sensor is 15° ×15°,the limiting star magnitude is 5. 6 m,the angular distance threshold between stars is 1°,and the number of navigation stars required for star map matching is15. The navigation star database constructed by this algorithm improves the uniformity of the navigation star′s distributions. In the necessary and sufficient sense of star map matching,the number of navigation stars in the star database reach the minimum. It thus reduces the number of matching pattern databases and reduces the memory requirements,which shows the engineering and practical value for the design of star sensors.
作者
王海涌
徐皓
Wang Haiyong;Xu Hao(School of Astronautics,Beihang University,Beijing 100191,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2021年第1期335-341,共7页
Laser & Optoelectronics Progress
基金
国家自然科学基金(61573113)。
关键词
天文光学
天文导航
星敏感器
导航星库
光轴随机矢量
astronomical optics
astronomical navigation
star sensor
navigation star database
optical random vector
