应用非线性优化算法自主标定星敏感器

叶涛; 杨飞

doi:10.3788/OPE.20172509.2483

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应用非线性优化算法自主标定星敏感器

信息科学 | 更新时间：2020-08-13

- 应用非线性优化算法自主标定星敏感器
- Autonomous calibration of star sensors based on nonlinear optimization algorithm
- 光学精密工程 2017年25卷第9期页码：2483-2489
- 作者机构：
  
  北京遥感设备研究所, 北京 100854
- 作者简介：
  
  [ "叶涛(1987-), 男, 湖北黄石人, 博士, 2009年、2012年于中国矿业大学分别获得学士、硕士学位, 2016年北京航空航天大学获博士学位, 现为北京遥感设备研究所工程师, 从事图像处理, 目标跟踪, 天文导航方面的研究.E-mail:ayetao198715@163.com" ]
  [ "杨飞(1980-), 男, 河南濮阳人, 硕士, 2002年、2006年于北京理工大学分别获得学士、硕士学位, 现为北京遥感设备研究所高级工程师, 从事天文导航方面的研究.E-mail:nick1980yang@163.com" ]
- 基金信息：
  
  北京遥感设备研究所批产产品资助项目(WA1F00)
- DOI：10.3788/OPE.20172509.2483
  中图分类号： V448.22
- 收稿日期：2017-04-21，
  
  录用日期：2017-5-19，
  
  纸质出版日期：2017-09-25
- 稿件说明：
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叶涛, 杨飞. 应用非线性优化算法自主标定星敏感器[J]. 光学精密工程, 2017,25(9):2483-2489.

Tao YE, Fei YANG. Autonomous calibration of star sensors based on nonlinear optimization algorithm[J]. Optics and precision engineering, 2017, 25(9): 2483-2489.
叶涛, 杨飞. 应用非线性优化算法自主标定星敏感器[J]. 光学精密工程, 2017,25(9):2483-2489. DOI： 10.3788/OPE.20172509.2483.

Tao YE, Fei YANG. Autonomous calibration of star sensors based on nonlinear optimization algorithm[J]. Optics and precision engineering, 2017, 25(9): 2483-2489. DOI： 10.3788/OPE.20172509.2483.

摘要

考虑传统的星敏感器标定方法忽略了星敏感器的畸变与光学参数之间的相互作用而引入的额外误差，提出了一种基于非线性优化的星敏感器自主标定算法。该算法首先忽略星敏感器畸变的影响，构建目标函数，利用Levenberg-Marquardt非线性优化算法优化星敏感器的光学参数；然后，将得到的光学参数估计值作为理想值，通过线性最小二乘法估计相机的镜头畸变系数；最后，将前两个步骤获得的参数作为初始值，构建目标函数，利用Levenberg-Marquardt算法同时优化光学参数和畸变系数。开展了仿真实验研究，并与最小二乘法和Samman法的标定结果做了对比，结果表明：提出的方法能够很好地实现星敏感器的自主标定。在同等测试条件下，文中算法获得的最大残差为0.015 pixels，精度高于其它两种标定方法两个数量级。星敏感器外场实验还表明，提出的优化方法有效提升了星敏感器的性能。

Abstract

Calibration methods of traditional star sensors ignore the additional errors from the interaction between optical parameters and distortion coefficients. This paper proposes an autonomous calibration algorithm based on nonlinear optimization to overcome the problems mentioned above. Firstly

the algorithm ignores the distortion to construct a target function

and the Levenberg-Marquardt nonlinear optimization algorithm is used to optimize the optical parameters of the star sensor. Then

the optimized optical parameter estimation iss used as the ideal value

and the lens distortion coefficient of the camera is estimated by the linear least square method. Finally

the parameters obtained by the first two steps are used as initial values to construct the target function

and the optical parameters and distortion coefficients are optimized by using Levenberg-Marquardt algorithm. Simulation and comparison experiments are performed in combination with least square method and Samman method

and results show that the maximum residual obtained by the algorithm is 0.015 pixels under the same test condition

and the accuracy is higher two orders of magnitude than that of the other two calibration methods. Moreover

the field experiments show that the proposed method effectively improves the performance of star sensors.

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references

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