为解决现有基于单星敏感器的星图识别中由于成像视角小，星图恒星数量不足而造成的星图识别率偏低的问题，提高星图识别的准确度和精确度，提出了一种基于多视场星敏感器的改进三角形星图识别方法；该方法通过将相同位置相同时间不同姿态角获得的多幅星图基于星图自身径向特征拼接成一幅多视角、不失真的星图，利用拼接后的星图进行星图识别，同时采用分块方式存储星对角距以及利用哈希查找提高星图识别效率；实验随机识别500幅星图，仿真结果表明，与传统的单视场星图匹配算法相比，该方法具有更高的星图识别率和匹配精度，当星图恒星数量达到30以上时，平均识别率能基本达到97％，且识别速度提高了11倍左右。%In order to solve the problem of the low star identification rate of the existing star pattern recognition based on one-FOV star sensor due to the small imaging perspective,the insufficient number of stars,improve the accuracy and precision of star identification,an im-proved triangle star identification method based on multi-FOV star sensor is proposed.The novel method stitches the pieces of star maps obtained in the same position and time but different attitude angle into a piece of star map which is multi-FOV and undistorted,and make use of the star map to complete the star identification.To improve the computation time,the angular of star identification based on block storage and Hash search are used to finish the star identification.500star maps are identified randomly and the simulation results show that compared with the traditional one-FOV star map,the novel algorithm has a higher rate of star identification and higher matching accuracy, the average identification rate can reach 97% when the number of stars are more than 30and identification time also improve 11times faster.
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