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为了快速高效地对星图进行识别,准确地完成天文导航任务,提出了一种基于剖分特征集星识别方法。首先使用星表数据建立数据库,三角剖分该数据库建立特征星库,再获取待识别星图剖分特征与已建立的特征星库相比较实现星识别。在改进海明相似度与Euclid相似度等相似方法基础上,提出了一种新的剖分特征集星识别法,使用该方法可以快速地找到一个很小的可能星集合,重复该方法再获得相邻星的可能星集合,两个星集合中赤经与赤纬最相近的就是识别星。实验显示使用剖分特征集星识别法,准确率可以达到97%以上,能够准确地完成星图识别任务。
In order to identify the star image quickly and efficiently and accomplish the task of astronomical navigation accurately, a method of star identification based on the feature of the subdivision is proposed. Firstly, a database is created by using the catalog data. The signature database is created by triangulation. The signature database is obtained by triangulation, and then the signature of the signature to be recognized is compared with that of the established signature database. On the basis of similar methods such as improving Heming similarity and Euclid similarity, a new method for identifying feature points in star clusters is proposed. By using this method, a very small possible star set can be quickly found, and then the method is repeated The possible star set of adjacent stars, the two stars in the set of the red and the declination is the most similar to identify the star. Experiments show that the use of segmentation feature set star recognition method, the accuracy rate can reach 97% or more, can accurately complete the task of identifying stars.