星图识别的一种扩充栅格算法  

An extended grid algorithm in star identification field

作　　者：钱华明[1] 孙龙[1] 蔡佳楠[1] 黄蔚[1] 

机构地区：[1]哈尔滨工程大学自动化学院,哈尔滨150001

出　　处：《哈尔滨工业大学学报》2015年第2期110-116,共7页Journal of Harbin Institute of Technology

基　　金：国家自然科学基金(61104036);哈尔滨市科技创新人才研究专项资金(2014RFXXJ074)

摘　　要：栅格算法作为一种鲁棒性好、识别率高的星图识别算法,要求星图中不少于6颗星才能进行正常的识别,限制了其在小视场或低星等敏感极限的星敏感器中的应用.针对这种情况,提出了星图识别的扩充栅格算法,该算法将扩充星图法与栅格算法结合,将视场进行有效地扩充,得到了更加丰富的星点信息,同时继承了栅格算法的优势,拥有比现有扩充星图法更强的噪声鲁棒性和更高的识别成功率.依据实际情况建立了仿真环境,并进行了大量实验,验证了算法的实时性和高识别率性能.结果表明:当应用于小视场星敏感器时,扩充栅格算法在位置噪声为1像素时的星图识别成功率大于97.4%,明显优于传统的扩充星图算法,同时其近邻星的识别成功率最高可达到86.7%,也明显优于传统栅格算法.扩充栅格算法更加适用于小视场或低星等敏感极限的星敏感器.The grid algorithm is an attractive one in star identification algorithms. However,this algorithm needs at least 6 stars in sensor image,which limits its application to the stellar sensor whose field of view（ FOV） is small or stellar magnitude limit is low. To break this limitation,a new algorithm named extended grid algorithm in star identification field is proposed. The ideas of the new algorithm is the combination of extended image algorithm and the grid algorithm,which can extend the FOV effectively,and then more stars will fall into the extended FOV. Additionally,the new algorithm inherits the advantages of grid algorithm,and its performance such as the stability and identification rate will be better than the extended image algorithm. To verify the performance of this new algorithm,a simulation according to the real situation is carried out. The results indicate that the star identification success ratio of the proposed method is larger than 97. 4%,it is better than the traditional extended image algorithm,and the neighbor star identification success ratio of the proposed method can reach 86. 7% which is also better than that of the traditional grid algorithm. Therefore,the proposed method is more applicable for the small FOV or low limiting magnitude stellar sensor.

关 键 词：星图识别 栅格算法 星敏感器 扩充星图法 小视场 

分 类 号：V249.3[航空宇航科学与技术—飞行器设计]