采用旋转不变特征的分步星图识别方法
2024,46(6):54-63
段辉
火箭军工程大学 导弹工程学院, 陕西 西安 710025，1020423896@qq.com,3199148797@qq.com
周召发
火箭军工程大学 导弹工程学院, 陕西 西安 710025，1020423896@qq.com,3199148797@qq.com
张志利
火箭军工程大学 导弹工程学院, 陕西 西安 710025
赵军阳
火箭军工程大学 导弹工程学院, 陕西 西安 710025
李新宇
火箭军工程大学 导弹工程学院, 陕西 西安 710025
闫兴旭
火箭军工程大学 导弹工程学院, 陕西 西安 710025
火箭军工程大学 导弹工程学院, 陕西 西安 710025，1020423896@qq.com,3199148797@qq.com
周召发
火箭军工程大学 导弹工程学院, 陕西 西安 710025，1020423896@qq.com,3199148797@qq.com
张志利
火箭军工程大学 导弹工程学院, 陕西 西安 710025
赵军阳
火箭军工程大学 导弹工程学院, 陕西 西安 710025
李新宇
火箭军工程大学 导弹工程学院, 陕西 西安 710025
闫兴旭
火箭军工程大学 导弹工程学院, 陕西 西安 710025
摘要：
针对星敏感器的空间迷失问题,提出了一种新的星图识别方法。利用距离映射矢量计算参考星与导航星之间的离散度,以缩短导航星库列表,得到候选导航星,再利用夹角特征矢量与距离特征矢量,通过相似度计算匹配出参考星唯一对应的导航星。通过对仿真星图和真实星图进行性能测试,评估其可行性。结果表明,方法对噪声具有较强的鲁棒性,在位置噪声、伪星和缺失星等恶劣环境的影响下仍能保证93.80%以上的识别率。
针对星敏感器的空间迷失问题,提出了一种新的星图识别方法。利用距离映射矢量计算参考星与导航星之间的离散度,以缩短导航星库列表,得到候选导航星,再利用夹角特征矢量与距离特征矢量,通过相似度计算匹配出参考星唯一对应的导航星。通过对仿真星图和真实星图进行性能测试,评估其可行性。结果表明,方法对噪声具有较强的鲁棒性,在位置噪声、伪星和缺失星等恶劣环境的影响下仍能保证93.80%以上的识别率。
基金项目：
国家自然科学基金资助项目(52075541)；陕西省自然科学基金资助项目(2022JM-243)
国家自然科学基金资助项目(52075541)；陕西省自然科学基金资助项目(2022JM-243)
Stepwise star map identification method using rotation-invariant features
DUAN Hui
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China,1020423896@qq.com,3199148797@qq.com
ZHOU Zhaofa
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China,1020423896@qq.com,3199148797@qq.com
ZHANG Zhili
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China
ZHAO Junyang
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China
LI Xinyu
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China
YAN Xingxu
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China,1020423896@qq.com,3199148797@qq.com
ZHOU Zhaofa
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China,1020423896@qq.com,3199148797@qq.com
ZHANG Zhili
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China
ZHAO Junyang
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China
LI Xinyu
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China
YAN Xingxu
College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China
Abstract：
A new star map identification method was proposed to solve the problem of space lost of star sensor. The distance mapping vector was used to calculate the dispersion between the reference star and the navigation star, in order to shorten the list of the navigation star database and obtain the candidate navigation star. The angle feature vector and the distance feature vector were used to match the unique corresponding navigation star of the reference star through the similarity calculation. The feasibility of this method was evaluated by the performance test of simulated star map and real star map. The results show that the proposed method is robust to noise and can guarantee the recognition rate of more than 93.80% under the influence of harsh environments such as location noise, pseudo stars and missing stars.
A new star map identification method was proposed to solve the problem of space lost of star sensor. The distance mapping vector was used to calculate the dispersion between the reference star and the navigation star, in order to shorten the list of the navigation star database and obtain the candidate navigation star. The angle feature vector and the distance feature vector were used to match the unique corresponding navigation star of the reference star through the similarity calculation. The feasibility of this method was evaluated by the performance test of simulated star map and real star map. The results show that the proposed method is robust to noise and can guarantee the recognition rate of more than 93.80% under the influence of harsh environments such as location noise, pseudo stars and missing stars.
收稿日期：
2022-06-14
2022-06-14
