Fast star tracking technology in star sensor
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摘要: 跟踪模式是星敏感器的主要工作模式之一,跟踪过程的快速性直接影响星敏感器的整体性能.提出了一种快速星跟踪算法.在跟踪算法的3个耗时环节,分别采用了分区星表、阈值映射、先排序后匹配识别这3种方法,以提高跟踪过程的快速性.其中分区星表法将整个天区分成了若干个子天区,使得在星体映射时,只是搜索星敏感器视轴指向附近的部分子天区,而不是搜索整个天区,减少了搜索星体的数量;阈值映射法,在满足精确度的情况下,设置被跟踪星体的数量阈值,只有被跟踪的星体数目少于此阈值时,才进行星体映射,减少了映射次数;先排序后匹配识别法,先根据星体在星图中的坐标值进行排序,然后再进行匹配识别,减少了那些距离较大的无谓的星体间的匹配识别.仿真测试结果表明,这3种方法的采用,提高了跟踪算法的快速性,提高了星敏感器的整体效能.Abstract: Tracking model is one of main models, when star sensor works. Speediness of tracking process affects star sensor′s performance. A fast star tracking algorithm was proposed. Three methods, such as star catalog partition, threshold mapping, sorting and matching, were designed for three time-consuming elements in tracking algorithm, in order to raise the tracking speed. Star catalog partition method divided the celestial sphere into some partitions. It made star mapping search in the partitions near the direction of star sensor′s visual axis not in the whole celestial sphere and reduced the total number of stars searched. Threshold mapping method in required accuracy condition, set a threshold of stars tracked. When the number of stars tracked was less than the threshold, star mapping was performed. It reduced mapping times. Sorting and matching method made sorting based on star′s coordinates in star image, and then matched. It avoided matching between stars which had a long distance. Simulation showed that application of these methods made this tracking algorithm faster, and improved the efficiency of star sensor.
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Key words:
- star image /
- star sensor /
- tracking algorithms /
- matching identification
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