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首页> 外文会议>International Conference on Signal Processing Systems >Fast Star Identification of Super Large Infrared Star Catalog
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Fast Star Identification of Super Large Infrared Star Catalog

机译：超大型红外星目录的快速明星识别

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For the high-sensitivity cameras of a super-large star catalog, the conventional effective star identification methods for star sensors will face huge storage and calculations that current computers cannot afford. This paper presents a two-stage full-sky star identification method. 3～4 prominent stars are firstly quickly identified from a simplified star catalog, to determine the view direction. Then, three different strategies are adopted to recognize other remaining stars in the field of view: one strategy is to automatically load the K-vector table of the corresponding sky zone; one strategy is to temporarily generate a K-vector table from the candidate star set, and then remaining stars are identified according to the angular distance from the prominent stars; the third strategy is to obtain the image coordinates of the candidate star set, the proximity position constraint is considered while constraining the angular distance from the prominent stars. Experiments show that the speed of the third strategy is increased by about 20% and maintains a higher recognition rate (F1 is about 0.92). This two-stage recognition method ingeniously resolves the huge amount of calculation caused by the super-large star catalog, and can identify enough stars (ten thousand stars) in a single frame, and provides sufficient control points for the subsequent intrinsic calibration.
机译：对于超大明星目录的高灵敏度相机，星形传感器的传统有效星形识别方法将面临巨大的存储和计算，即当前计算机无法承受。本文介绍了两级全天星识别方法。首先从简化的星星目录中快速识别3〜4突出恒星，以确定视图方向。然后，采用三种不同的策略来识别视野中的其他剩余恒星：一个策略是自动加载相应天空区域的K矢量表;一种策略是临时生成来自候选星集的K矢量表，然后根据突出恒星的角度距离识别剩余的恒星;第三策略是获得候选星组的图像坐标，在约束与突出恒星的角度距离约束的同时考虑接近位置约束。实验表明，第三种策略的速度增加了约20％并保持较高的识别率（F1约为0.92）。这种两级识别方法巧妙地解决了超大型星期星目录引起的大量计算，并且可以在单个框架中识别足够的恒星（万颗星），并为随后的内在校准提供足够的控制点。

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