A blurred star image restoration method based on gyroscope data and enhanced sparse model

被引:3
作者
Yi, Jinhui [1 ,2 ,3 ,4 ]
Ma, Yuebo [1 ,2 ,3 ]
Zhu, Zifa [1 ,2 ,3 ]
Zhu, Zijian [1 ,2 ,3 ]
Tang, Yuping [1 ,2 ,3 ]
Zhao, Rujin [1 ,2 ,3 ]
机构
[1] Natl Key Lab Opt Field Manipulat Sci & Technol, Chengdu 610209, Peoples R China
[2] Chinese Acad Sci, Inst Opt & Elect, Chengdu 610209, Peoples R China
[3] Chinese Acad Sci, China Key Lab Sci & Technol Space Optoelect Precis, Chengdu 610209, Peoples R China
[4] Univ Chinese Acad Sci, Sch Elect Elect & Commun Engn, Beijing 100049, Peoples R China
基金
中国科学院西部之光基金;
关键词
star sensor; dynamic environment; gyroscope; image restoration; enhanced sparse model; PERFORMANCE; SENSOR;
D O I
10.1088/1361-6501/ace730
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Star sensors usually have a fixed exposure time to guarantee detection of adequate navigation stars. In a high dynamic environment, star images suffer from degradation due to spacecraft movement, which will severely affects both centroid extraction and attitude accuracy. This paper presents an algorithm for the restoration of motion-blurred star images. The algorithm employs gyroscope assistance and consists of two steps: preprocessing and motion-blurred image restoration. In the preprocessing step, the angular velocity of the gyroscope predicts the motion trajectory, position, and shape of each star point during exposure. This step ensures a good initial estimate of the blur kernel for image restoration. The image restoration step employs an enhanced sparse model inspired by blind deblurring method to solve blur kernel and latent image alternately. Simulations and experiments have verified the effectiveness of the proposed algorithm.
引用
收藏
页数:12
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