基于交叠视场亮度优选算法的导航星库构建方法

星敏感器导航星库直接影响星图识别效率和姿态解算精度。分析了参与姿态解算的星颗数和亮度对姿态精度影响,在此基础上,提出了一种基于交叠视场亮度优选算法的星敏感器导航星库构建方法。将精度较高的Hipparcos星表作为基础星表,分析了星等、双星、自行、变星等对姿态精度的影响,将星库筛选成一个备选星库,生成覆盖全天球的交叠视场。每个拥有较多星的视场,都按照亮度优先原则从视场内的扇形区域中选择导航星,从而得到分布均匀的导航星库。结果表明:该方法能有效减小星敏感器导航星库规模,实现导航星在全天球和局部天区的均匀分布。

Guide Star Database Creation for Star Sensor Based on Overlapping Field of View and Intensity Priority Selection Algorithm

Guide star database creation for the star sensor will have effects on star map identification time and attitude determination accuracy. Based on the analysis of the influence of star number of attitude determination and intensity on attitude accuracy, an algorithm of guide star database creation for the star sensor based on overlapping field of view (FOV) and intensity priority selection is proposed. Hipparcos which has high accuracy is selected as the basic table, the influence of star magnitude, double-star, proper motion and variable star on attitude accuracy has been analyzed, and then an alternative star database is screened out. In order to get an evenly distributed guide star database, overlapping FOVs covering all over the celestial sphere are generated to select the guide star in the fan section of the FOV which has many stars, according to the intensity priority selection principle. The experimental results show that the proposed method can not only effectively reduce the number of guide stars, but also realize uniform distribution of guide stars in the whole and partial celestial sphere.