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基于三轴转台的多视场星敏感器标定方法
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  • 英文篇名:Calibration method for multiple FOV star sensors based on three-axis turntable
  • 作者:熊琨 ; 王春喜 ; 吴跃 ; 王锴磊 ; 姜云翔
  • 英文作者:Xiong Kun;Wang Chunxi;Wu Yue;Wang Kailei;Jiang Yunxiang;Beijing Aerospace Institute for Metrology and Measurement Technology;
  • 关键词:星敏感器 ; 标定 ; 多视场 ; 结构模型
  • 英文关键词:star sensor;;calibration;;multiple FOV;;structure model
  • 中文刊名:HWYJ
  • 英文刊名:Infrared and Laser Engineering
  • 机构:北京航天计量测试技术研究所;
  • 出版日期:2018-12-13 16:50
  • 出版单位:红外与激光工程
  • 年:2019
  • 期:v.48;No.294
  • 语种:中文;
  • 页:HWYJ201904035
  • 页数:6
  • CN:04
  • ISSN:12-1261/TN
  • 分类号:242-247
摘要
提出了一种基于三轴转台的多视场星敏感器标定方法。该方法利用转台的3个旋转自由度,无需重新安装即可对任意轴向的视场进行标定数据采集。通过对于测量模型、结构参数模型及外参数模型的建模及优化整合得到实验室标定模型。使用Levenberg-Marquardt非线性最小二乘法求解各视场的测量模型参数和各视场间的结构模型参数。该方法无需通过外场观星数据确定结构模型参数,大大节省了标定数据采集的工作量,也避免了大气对恒星矢量的影响引入的参数估计误差。通过一台数字三视场星敏感器的仿真试验和一台双视场星敏感器样机的实际试验验证了该方法的有效性。与基于外场观测的传统方法相比,视场内星间平均角距误差减小了20.32%,视场间星间角距平均误差减小了59.34%。
        A novel calibration method for multiple FOV star sensors based on three axis turntable was proposed. The method mainly took advantages of the turntable′s three rotational freedom degrees to calibrate FOVs of arbitrary directions without reinstalling the sensor. Modeling for laboratory calibration was achieved through optimizing and trimming of the observation model, the structure model and the external parameter model. The observation model parameters of each FOV and the structure model parameters among distinct FOVs were solved by the Levenberg-Marquardt nonlinear least square algorithm. Without the need of outfield star observation in the calibration process of structure model parameters, huge amount of data sampling work load was saved, hence, the estimation error caused by the atmosphere refraction and disturbance phenomena was avoided. The validity of the method was demonstrated by the simulation of a triple FOV digital star sensor and the real experiment of a dual FOV star sensor. Compared to the conventional method that utilizes outfield star observation data, the average angle distance error within single FOV reduces by 20.32%, and the average angle distance error between FOVs reduces by 59.34%.
引文
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