摘要
星敏感器是现代航天领域中一种高精度的卫星姿态测量仪器,自主导航星敏感器能在太空中任意位置快速测量姿态,无须先验姿态信息。研究其关键技术,对于奠定开发稳定、快速的高性能自主导航星敏感器技术基础有重要意义。
第一章阐述论文所研究的问题,研究它的意义和应用价值,介绍国内、外星敏感器的研究现状。
第二章介绍星敏感器采用的相关坐标系和星表等概念,论述自主导航星敏感器的组成和工作原理。
第三章依据自主导航要求,详细分析和给出光学系统的视场、焦距和口径等参数的相互关系、确定方法和实例。
第四章研究星敏感器星像提取算法。介绍十字链表结构和区域增长算法,提出和实现十字链表像元聚类快速星像提取算法,以缩短提取星像的时间。
第五章研究导航星优选算法以及星图识别算法。通过分析全天球恒星分布特点,提出多尺度像面分割(Multi-scale image plane segmentation,简称MIPS)导航星优选算法,以使导航星分布均匀。为了降低伪星和星像提取误差引起的星图误识别率,研究和改进金字塔星图识别算法,提出五角星星图识别算法,完成其程序。通过处理模拟星图,评价和验证MIPS算法和五角星算法的性能与有效性。
第六章介绍利用现有光学设计软件扩展接口模拟星场成像的方法,给出模拟结果,验证其正确性。获得的模拟星图适用于星像提取、导航星优选和星图识别算法研究。
第七章进行自主导航星敏感器关键技术的验证实验。介绍和给出实验方法、装置和结果。验证本论文述及的光学系统参数确定方法、十字链表像元聚类快速星像提取算法、MIPS导航星优选算法、五角星星图识别算法等自主导航星敏感器关键技术。最后,总结论文主要内容和创新点,展望下一步需要开展的工作。
Star sensor is a high precise attitude measurement instrument for satellites in the fieldof modern spaceflight. Autonomous star sensor measures attitudes very fast in any positionof space without any apriori information. Study on its key technologies has significancesfor laying the technical foundation for development of autonomous star sensors with highstability, update rate, and performance.
In chapter one, the issue studied in this dissertation, its significance and applicationare put forward. The state of art of star sensors at home and abroad is introduced.
In chapter two, the concepts of the associated coordination systems and star catalogsused in star sensors are introduced. The constructions and the working principles ofautonomous star sensors are discussed.
In chapter three, according to the requirements for autonomous navigation,relationships, determination and examples of optical system performances such as the fieldof view, the focal length, and the entrance pupil diameter and so on, are analyzed and givenout in detail.
In chapter four, star image extraction algorithms are studied. Cross-link list structureand region-growing algorithm are introduced. A fast star image extraction algorithm basedon cross-link list and pixel clustering is presented and realized in order to save the time toextract star images.
In chapter five, optimal selection algorithm for guide stars and star patternidentification algorithm are studied through analyzing distribution characteristics of starsover the celestial sphere. The optimal selection algorithm based on the Multi-scale ImagePlane Segmentation (MIPS) is proposed in order to have them uniformly distribute. Inorder to reduce the wrong identification rate as a result of false stars and star imageextraction errors, Pentagram star pattern identification algorithm is proposed andprogrammed through investigation and improvement of conventional Pyramid algorithm.The performances and the validities of MIPS and Pentagram algorithms are evaluated bymeans of processing simulated star maps.
In chapter six, a method to simulate the imaging of star fields is introduced utilizingthe extension interface of available optical design program. The simulation results aregiven out, and their correctness is tested. The simulated star maps are suitable to study onthe star image extraction algorithm, optimal selection algorithm for guide stars and starpattern identification algorithm.
In chapter seven, the verifying experiment of the key technologies relative toautonomous star sensors is implemented. The experimental methods, setups and results areintroduced and reported respectively. The key technologies researched in this dissertationincluding the method to determine the performances of optical system, star imageextraction algorithm based on cross link list and pixel clustering, MIPS optimal selectionalgorithm for guide stars, Pentagram star pattern identification algorithm are verified.
Finally, the main work and the innovative aspects in this dissertation are summarized,and the further research is prospected.
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