面向光轴指向测量系统的光斑质心高精度实时解算方法
DOI:
CSTR:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

TH712

基金项目:

北京学者计划研究项目(BJXZ2021-012-00046)资助


High-precision real-time algorithm for spot centroid determination in optical axis pointing measurement system
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对遥感卫星相机光轴指向测量系统的 CMOS 图像传感器易受空间环境影响,导致图像缺陷,进而影响光斑质心解算 精度的问题,本文提出了一种高精度的光斑质心实时解算方法。 仿真分析结果表明该方法能够准确地追踪图像中光斑位置的 变化,从而验证了其分步解算策略的可行性。 分别采用分步法、OTSU 质心法和高斯拟合法对测量系统所采集的图像进行光斑 质心的实时解算。 实验结果显示,分步法的实时性好,光斑识别成功率最高,质心解算平均偏差和标准差最小,分别为 0. 026 和 0. 029 pixels。 该方法可以为光轴指向测量系统提供可靠的数据支撑。

    Abstract:

    The images produced by the CMOS sensor of the high-orbit satellite′s optical axis pointing measurement system are prone to degradation due to the harsh space environment. This degradation adversely affects the quality of the images and compromises the accuracy of the spot centroid results. To combat this issue, this study proposes a method for high-precision, real-time determination of spot centroid. Simulation analysis results show that this method can accurately track changes in the spot position within images, validating the feasibility of its step-by-step calculation strategy. The study employed the progressive method, OTSU centroid method, and the Gaussian fitting method for the real-time computation of spot centroids from images acquired by the measurement system. The experimental results show that the progressive method has good real-time performance, the highest success rate of spot location, and the smallest average deviation and standard deviation of centroid calculation, being 0. 026 and 0. 029 pixels, respectively. This approach provides reliable data support for optical axis pointing measurement systems.

    参考文献
    相似文献
    引证文献
引用本文

马浚轩,李 红,张 旭,朱云鸿,祝连庆.面向光轴指向测量系统的光斑质心高精度实时解算方法[J].仪器仪表学报,2024,45(6):266-273

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2024-11-25
  • 出版日期:
文章二维码