Sub-pixel subdivided model for retro-reflection spot positioning algorithm

doi:10.3788/OPE.20162413.0575

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Sub-pixel subdivided model for retro-reflection spot positioning algorithm

更新时间：2020-08-13

- Sub-pixel subdivided model for retro-reflection spot positioning algorithm
- Optics and Precision Engineering Vol. 24, Issue 10s, Pages: 575-582(2016)
- 作者机构：
  
  1. 上海交通大学电子信息与电气工程学院上海,200240
  2. 上海宇航系统工程研究所上海,201108
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20162413.0575
  CLC： TP314.7;TP873
- Received：10 June 2016，
  
  Revised：12 June 2016，
  
  Published：14 November 2016
- 稿件说明：
移动端阅览
邓凯鹏, 赵辉, 彭福军等. 逆反射光斑定位算法的亚像素细分模型[J]. 光学精密工程, 2016,24(10s): 575-582

DENG Kai-peng, ZHAO Hui, PENG Fu-jun etc. Sub-pixel subdivided model for retro-reflection spot positioning algorithm[J]. Editorial Office of Optics and Precision Engineering, 2016,24(10s): 575-582
邓凯鹏, 赵辉, 彭福军等. 逆反射光斑定位算法的亚像素细分模型[J]. 光学精密工程, 2016,24(10s): 575-582 DOI： 10.3788/OPE.20162413.0575.

DENG Kai-peng, ZHAO Hui, PENG Fu-jun etc. Sub-pixel subdivided model for retro-reflection spot positioning algorithm[J]. Editorial Office of Optics and Precision Engineering, 2016,24(10s): 575-582 DOI： 10.3788/OPE.20162413.0575.

摘要

在大型空间桁架结构振动和平面度测量中，大尺寸远距离的空间定位测量需求十分普遍，考虑其距离远，范围大，精度高的测量特点，光斑定位是最优方法之一。本文介绍一种基于逆反射靶标以形成与背景对比度较大的逆反射圆形光斑，并采用计算机视觉等相关算法实现精度细分的远距离定位。算法对逆反射光斑采用梯度Canny算子进行边缘提取，对边缘进行最小二乘拟合得到光斑圆心坐标来实现定位。文章通过对Canny算子边缘检测误差和最小二乘拟合精度进行细分建模，分析光斑定位的重复性误差界，给出该算法光斑定位重复性精度的可靠估计。在LED和532nm激光分别作为光源实验中，圆心定位3-sigma重复性误差界分别为0.30 mm和0.57 mm，与细分模型得到的

倍的细分估计吻合。通过最小二乘圆拟合对Canny算子提取边缘结果的精度细分，能够满足远距离空间定位的高精度要求。

Abstract

With regard to the measurement for vibration and flatness of large-scale space truss structure

the demand in large-scale and long-distance space positioning measurement is very common

and in consideration of the measurement characteristics of long distance

large scale and high precision

spot positioning is regarded as one of the optimal methods. In this paper

a kind of round spot based on retro-reflection target

with a relatively large target-background contrast

is introduced; and related algorithm such as computer vision is adopted to realize the long-distance positioning with precision subdivision. By virtue of the Canny edge detector

edge extraction is conducted in the retro-reflected spot and coordinate of the spot center is worked out through least-square fitting in the edge

thus achieving the positioning purpose. Through subdivided modeling for the Canny edge detection error and least-square fitting precision

an analysis is conducted on the repeatability error bounds of the spot positioning

and a reliable estimation for repeatability precision of spot positioning in this algorithm is provided. In the experiment where LED and 532 nm laser is taken as the light source

the repeatability error bounds of the center positioning 3-sigma are respectively 0.30 mm and 0.57 mm

which are consistent with the

estimate obtained in the subdivided model. Precision subdivision of the extracted edge by Canny edge detector through the least-square circle fitting can satisfy the requirement for high precision in long-distance space positioning.

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references

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