舰船导航用星体自动识别技术研究

导航星星库的容量、存储内容是影响星图识别时间和识别率的关键因素。引入了动态星等阈值分布函数，将传统星等阈值过滤算法中的静态阈值用动态星等阈值代替，建立了一种新的动态星等阈值过滤选择模式。实验表明，用该算法所选取的导航星数量少，分布均匀性好，具有很强的通用性。在此基础上给出了基于主星的导航三角形星图构造方法，提高了星图识别敢率；提出了一种基于证据理论星图识别方法，可以解决传统三角形算法的冗余匹配问题，提高了星图识别的准确性。

Star Field Recognition for Ship''''s Navigation

The capacities, store content of the guide star catalog are key factors that influence the time and efficiency of star field recognition. To generate a desirable mission catalog, a novel method for automatic selection of guide star and regression selection algorithm is presented. With the creation of distribution function of dynamic visual magnitude threshold (VMT), the static VMT in traditional visual magnitude filtering method is replaced by dynamic VMT. The experiment results demonstrate that the guide star catalog identified by the proposed algorithm has fewer total numbers, smaller catalog size and better distribution uniformity, etc.. The paper introduces the structure of triangle based on primary bright stars. It has the higher rate of star field recognition. A method that applies the evidence theory to star recognition is presented. It can solve the redundancy match of the traditional triangle algorithm and to improve the probability of accurate recognition.