摘要
星图识别算法是星敏感器输出姿态的关键技术。根据星图从天球坐标系转换到星敏感器坐标系过程中存在特征值不变的原理,结合视场和星等需求建立了导航星表。并根据星图识别要求设计了对应的快速识别算法。针对特征表维数多的特点,采用K向量法提高搜索效率,同时采用并行计算的思想进一步提高搜索速度。采用Matlab编程实现了算法,并进行了仿真。结果表明,算法的识别效率可达97.8%,平均搜索时间可达14.4ms,能够满足准确率高、识别速度快的要求。
Star identification algorithm is the key technology for star tracker to get attitude.A navigation star catalog was set up according to the feature value unchanged theory from celestial coordinate system to star tracker coordinate system,with the requirements of field of view（FOV）and visual magnitude.Finally corresponding fast star identification was designed.Kvector method was employed to improve search efficiency due to six-dimensions feature table,and parallel computing was used to speed up searching.The algorithm was realized and simulated with Matlab.The simulation results demonstrate that star identification success rate is up to97.8%,and average searching time is 14.4 ms, which meets the requirements of high identification accuracy rate and fast identification rate.
出处
《半导体光电》
CAS
北大核心
2018年第1期113-117,共5页
Semiconductor Optoelectronics
基金
国家自然科学基金项目(40776100)
关键词
星图识别
特征不变
K向量
并行计算
star identification
unchanged feature
K-vector
parallel computing
