全天自主星图识别网格算法问题分析与改进

唐武盛; 杨建坤; 衣文军; 贾辉; 程攀攀

doi:doi:10.3788/lop53.021002

激光与光电子学进展, 2016, 53 (2): 021002, 网络出版: 2016-01-22

全天自主星图识别网格算法问题分析与改进下载： 1300次

Analysis and Improvement of the Grid Algorithm for Autonomous Star Identification

论文大纲

唐武盛 ^*杨建坤衣文军贾辉程攀攀

作者单位

国防科学技术大学理学院, 湖南长沙 410073

AI 词云图 AI一句话精读 AI短摘要

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摘要

在观测星数量较少时，匹配星数和边界距离的判定条件达不到网格法要求，同时由于网格法算法本身的原理局限，造成识别率明显下降。针对此问题提出一种改进的网格算法，在保证稳健性的前提下，有效提高星点识别率。实验结果表明，采用该算法，在星点数量少于10 颗的条件下，星点识别率从传统网格算法的95%提高到99%。同时，针对星图中未识别和误识别的星点进行的分析，能够为今后网格识别算法的进一步改进提供帮助。

Abstract

When the number of observed stars is few, the matching number of stars and the decision conditions of boundary distance do not satisfy the requirement the grid algorithm. Meanwhile because of the principle limits of the grid algorithm, the identification rate decreases obviously. According to these problems, an improved grid algorithm is put forward, and the identification rate of observed star increases effectively in precondition of ensuring the robustness. Experimental results show that the improved grid algorithm urges the identification rate increased from 95% to 99% compared with the traditional grid algorithm, under the condition that the number of observed star is less than 10. At the same time, the non-recognition and false-recognition stars in the star chart have been carried on the analysis, it can help to promote grid algorithm for star identification further.

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唐武盛, 杨建坤, 衣文军, 贾辉, 程攀攀. 全天自主星图识别网格算法问题分析与改进[J]. 激光与光电子学进展, 2016, 53(2): 021002. Tang Wusheng, Yang Jiankun, Yi Wenjun, Jia Hui, Cheng Panpan. Analysis and Improvement of the Grid Algorithm for Autonomous Star Identification[J]. Laser & Optoelectronics Progress, 2016, 53(2): 021002.

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