Study on Optimal Selection Algorithm of Guide Stars Based on Star Clustering for Star Sensors[J]. 2018, 35(3): 140-144.DOI:
Study on Optimal Selection Algorithm of Guide Stars Based on Star Clustering for Star Sensors
摘要
讨论恒星星座特征
分析Mean Shift算法原理
提出根据恒星的惯性坐标系位置
以星对角间距为特征
通过迭代将当前视场内恒星划分星座的思想
设计基于星座聚类优选导航星的算法
详细说明具体的实施步骤.以SAO星表为原始星数据
开展了可见光波段导航星优选实验.实验表明
提出的导航星优选算法
计算简单
易于实现
所得导航星分布均匀性优于MIPS、正交网格等算法.
Abstract
Star cluster features are discussed. The algorithm of Mean Shift is analyzed. The idea that distributes stars in the location field of view to clusters is proposed by iterative operation using the characteristic of star pair angular separations according to the star positions in the inertial coordinate system. The optimal selection algorithm of guide stars based on star clustering is designed. Its detailed implement procedures are introduced completely. The guide star optimal selection experiment in visible band by using SAO star catalog as the original star data is fulfilled. It proves that the proposed algorithm has the virtue of simple calculation and easy realization. The obtained guide star distribution is more uniform than the MIPS algorithm and the grid algorithm.