首页|基于模型和样条的星敏感器在轨自标定方法

基于模型和样条的星敏感器在轨自标定方法

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星敏感器长期在轨运行时,畸变会逐渐积累,因此对星敏感器进行在轨标定很有必要。目前,大多数星敏感器在轨标定算法仅依赖于星间角距的不变性,并需要较长的标定时间。本文算法的创新性在于利用星间角距关系和星点像素位置关系,将畸变信息解耦为粗校准的参数化信息和精校准的非参数化信息。充分考虑到星敏感器的工作性质,利用B样条算法的特点,使得连续的在轨校正仅需极少的时间。相较于目前常用的地面标定算法,本文算法在实现更准确的星点位置校正和更精确的姿态输出精度的前提下,训练完全部数据只需要几百毫秒的时间。在经过本文算法的标定后,在轨星敏感器的星点位置偏差由0。55766 pixel降低为0。23706 pixel,测量精度由5。857"提高到2。775",这为未来低成本卫星搭载非专业化设计的星敏感器提供了一定的算法参考。
On-Orbit Self-Calibration Method for Star Sensors Based on Models and Splines
Objective Lens distortion is a common problem in the optical system of star sensors.Vibrations during launch,changes in the space thermal environment,and other factors may cause changes in the optical system and lead to lens distortion.The changes in the optical system include the refractive index changes of optical materials,the thickness,curvature radius,and surface shapes of optical lenses,and the distance changes between optical elements.These distortions can change the focal length and principal point and can cause various nonlinear distortions of the optical system,leading to errors in the angle information obtained in the star sensor,thereby affecting the accuracy of navigation and attitude control.These errors may accumulate in long-duration missions and lead to poor system performance.Therefore,eliminating lens distortion and improving the measurement accuracy of star sensors become necessary for maintaining the attitude output accuracy of star sensors.Methods In response to the accumulation of lens distortion in star sensors due to mechanical vibrations,temperature changes,radiation,and solar radiation pressure during launch,as well as poor attitude accuracy caused by the optical distortion of uncalibrated low-cost cameras,we creatively introduce the non-parameterized B-spline algorithm into the widely used model-based correction algorithm.This approach decouples lens distortion into parameterized coarse calibration and non-parameterized fine calibration.The main advantage of B-spline curves is their flexibility and local controllability.Compared to the traditional interpolation methods,the shape of B-spline curves can be controlled locally by adjusting the positions of control points without affecting the entire curve.In the coarse calibration stage,the Levenberg-Marquardt algorithm is introduced to optimize the principal point and focal length,and the results are used as parameters for data preprocessing.Additionally,the right ascension,declination,and rotation angle of each frame image are also used as inputs.After the data preprocessing,the pixel coordinates of each star point on the image plane are produced.Lastly,a multi-layered structure of bicubic B-spline grids is constructed,achieving sound correction of global distortion and addressing local nonlinear distortions.This approach reduces the requirements for lens manufacturing and improves the attitude accuracy of on-orbit star sensors.Results and Discussions We conduct a simulation to simulate various distortion situations that may occur(Table 2),determine the optimal number of layers for the B-spline grid(Fig.5),and verify the compensation ability of the non-parameterized B-spline algorithm for distortion(Fig.6).In terms of distortion correction and time consumption,comparisons are made with the BP network algorithm optimized by genetic algorithm and neural network algorithm.Simulation experiments show that B-splines can effectively handle various distortions of star sensor lenses with theoretically high accuracy(Table 3).Compared with the neural network algorithm and genetic algorithm,our algorithm achieves attitude output accuracy at the sub-arcsecond level after correction,which is an order of magnitude better than the arcsecond level accuracy of the neural network algorithm and genetic algorithm(Table 4).To verify the on-orbit feasibility of the algorithm,850 images transmitted from a star sensor of a remote-sensing satellite in the sun-synchronous orbit are selected for calibration testing.After the calibration with this algorithm,the position deviation of star points is reduced from 0.55766 to 0.23706 pixel(Table 6),and the measurement accuracy is improved from 5.857"to 2.775",demonstrating high feasibility.Compared with common ground calibration algorithms,this algorithm shows higher calibration accuracy and requires only a few hundred milliseconds to train all data.Conclusions This paper proposes a rapid spline-based on-orbit self-calibration method,which decouples distortion into parameterized coarse calibration and non-parameterized fine calibration.Through the design of the B-spline grid and the self-calibration algorithm,fast and accurate correction of star-sensor distortion is achieved.Through simulation and on-orbit experiments,the effectiveness and robustness of the method are proved.This research provides an effective method to improve attitude accuracy in on-orbit self-calibration of star sensors.It also provides theoretical and experimental foundations for the development of cost-effective star sensors.

star sensoroptical distortionon-orbit calibrationB-spline algorithmimage processing

闫浩东、支帅、陈旭睿、李照雄、丁国鹏、张洋洋、张永合、朱振才

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中国科学院微小卫星创新研究院卫星数字化重点实验室,上海 201210

中国科学院大学,北京 100049

上海科技大学信息科学与技术学院,上海 201210

星敏感器 光学畸变 在轨标定 B样条算法 图像处理

2024

光学学报
中国光学学会 中国科学院上海光学精密机械研究所

光学学报

CSTPCD北大核心
影响因子:1.931
ISSN:0253-2239
年,卷(期):2024.44(12)