Application Research on Support Vector Machines in Optimal Selection of Guide Star
基于支持向量机的导航星选取算法研究*

The optimal selection of the guide star is important and necessary to generate the on-board guide star catalog since the number of the stars is too large to be fitted with the star tracker. The existing general selection procedures of the guide star, based on the large number of enumeration and many times iteration, are usually complicated and time-consuming, and the result generated by these selection methods is not always optimal. The Support Vector Machines ( SVM) based on the Statistical Learning Theory ( SLT) can solve this problem. SVM and SLT provide us a new approach to develop the simplified procedure of guide star automatic selection. The classification selection algorithm of the guide star using the SVM is discussed in this paper and the classifier of the guide star is obtained. Experiments on selection of the guide star are conducted and the results demonstrate that the SVM-based classifier of guide star has high adaptability for the automatic selection of the guide star.