| 一种基于星点特征不变原理的快速星图识别方法 |
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| 引用本文： | 张旭旭,尹达一.一种基于星点特征不变原理的快速星图识别方法[J].半导体光电,2018,39(1):113-117. |
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| 作者姓名： | 张旭旭 尹达一 |
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| 作者单位： | 中国科学院上海技术物理研究所中国科学院红外探测与成像技术重点实验室,上海200083;中国科学院大学,北京100039;中国科学院上海技术物理研究所中国科学院红外探测与成像技术重点实验室,上海,200083 |
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| 基金项目： | 国家自然科学基金项目(40776100) |
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| 摘 要： | 星图识别算法是星敏感器输出姿态的关键技术。根据星图从天球坐标系转换到星敏感器坐标系过程中存在特征值不变的原理,结合视场和星等需求建立了导航星表。并根据星图识别要求设计了对应的快速识别算法。针对特征表维数多的特点,采用K向量法提高搜索效率,同时采用并行计算的思想进一步提高搜索速度。采用Matlab编程实现了算法,并进行了仿真。结果表明,算法的识别效率可达97.8%,平均搜索时间可达14.4ms,能够满足准确率高、识别速度快的要求。
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| 关 键 词： | 星图识别 特征不变 K向量 并行计算 |
| 收稿时间： | 2017/6/30 0:00:00 |
A Novel Fast Star Pattern Identification Method Based on Unchanged Feature Theory |
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| ZHANG Xuxu,YIN Dayi.A Novel Fast Star Pattern Identification Method Based on Unchanged Feature Theory[J].Semiconductor Optoelectronics,2018,39(1):113-117. |
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| Authors: | ZHANG Xuxu YIN Dayi |
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| Abstract: | Star identification algorithm is the key technology for star tracker to get attitude. A navigation star catalog was set up according to the feature value unchanged theory from celestial coordinate system to star tracker coordinate system, with the requirements of field of view(FOV) and visual magnitude. Finally corresponding fast star identification was designed. K-vector method was employed to improve search efficiency due to six-dimensions feature table, and parallel computing was used to speed up searching. The algorithm was realized and simulated with Matlab. The simulation results demonstrate that star identification success rate is up to 97.8%, and average searching time is 14.4ms, which meets the requirements of high identification accuracy rate and fast identification rate. |
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| Keywords: | star identification unchanged feature K-vector parallel computing |
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