基于GDOP贡献值递推的自动天文选星算法

Automatic Astronomical Star Selection Algorithm Based on GDOP Contribution Value Recursion

传统天文测量依赖人工选星,自动化程度不高,难以快速选出具有最优几何分布的恒星观测组合,因而存在测量效率低、定位精度易受作业员影响等突出问题。为此,提出一种基于GDOP贡献值递推的自动天文选星算法。首先,构建GDOP贡献值的数学模型,确定递推选星策略,实现自动化选星;其次,利用GDOP值定量评估恒星观测组合的几何分布特性,经可测性分析后编制出具有最优几何分布的观测星表。相比于人工选星,恒星观测组合的GDOP值减小0.025,优化了恒星观测组合的几何分布;每个观测时段测量耗时由29 min减少到12 min,测量效率提高58.6%。所设计的算法性能良好,且可实现自动化,具有较好的应用前景。

Traditional astrometry relies on artificial star selection,which is not highly automated,and it is difficult to quickly select the star observation combination with the optimal geometric distribution.Therefore,there are some prominent problems,such as low measurement efficiency,positioning accuracy easily affected by operators and so on.Based on the recursive algorithm of GDOP,an automatic star selection algorithm is proposed in the paper.Firstly,the mathematical model of GDOP contribution value is constructed,the recursive star selection strategy is determined,and the automatic star selection is realized.Then,the geometric distribution characteristics of star observation combination are quantitatively evaluated by using GDOP value,and the observation catalogue with optimal geometric distribution is compiled after testability analysis.Compared with the traditional artificial star selection,the GDOP value of star observation combination decreases by 0.025,which optimizes the geometric distribution of star observation combination.The measurement time for each observation period is reduced from 29 min to 12 min,and the measurement efficiency is increased by 58.6%.The algorithm has good performance and can be automated,which has a good application prospect.