采用多站图像直线特征的飞机姿态估计

王彬; 何昕; 魏仲慧

doi:10.3788/OPE.20132107.1831

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采用多站图像直线特征的飞机姿态估计

信息科学 | 更新时间：2020-08-12

- 采用多站图像直线特征的飞机姿态估计
- Attitude estimation of aircrafts using line features on multi-camera images
- 光学精密工程 2013年21卷第7期页码：1831-1839
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院大学北京,中国,100049
- 作者简介：
- 基金信息：
  
  江苏省普通高校研究生科研创新计划基金资助项目()
- DOI：10.3788/OPE.20132107.1831
  中图分类号： TP391;V448.22
- 收稿日期：2012-05-29，
  
  修回日期：2012-07-09，
  
  网络出版日期：2013-07-15，
  
  纸质出版日期：2013-07-15
- 稿件说明：
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何昕王彬魏仲慧. 采用多站图像直线特征的飞机姿态估计[J]. 光学精密工程, 2013,21(7): 1831-1839

WEI Zhong-hui. Attitude estimation of aircrafts using line features on multi-camera images[J]. Editorial Office of Optics and Precision Engineering, 2013,21(7): 1831-1839
何昕王彬魏仲慧. 采用多站图像直线特征的飞机姿态估计[J]. 光学精密工程, 2013,21(7): 1831-1839 DOI： 10.3788/OPE.20132107.1831.

WEI Zhong-hui. Attitude estimation of aircrafts using line features on multi-camera images[J]. Editorial Office of Optics and Precision Engineering, 2013,21(7): 1831-1839 DOI： 10.3788/OPE.20132107.1831.

摘要

在角平分线方向向量法基础上提出了一种新的基于直线特征的飞机姿态多站测量方法。首先，用角平分线方法计算飞机的中轴线及其共面垂线的方向向量，由此得到飞机参考系到经纬仪摄像机参考系的旋转矩阵。然后，提取所有测站经纬仪图像上机翼边缘的直线特征，联合经纬仪俯仰方位角等参数，推导出直线特征的目标空间共面总误差函数，并使用改进的正交迭代方法优化旋转矩阵使总误差最小。最后，分解优化后的旋转矩阵得到飞机的姿态值。仿真实验得到的四站测量精度为0.17，图像处理速度为32 frame/s，比角平分线法有了大幅的提高，另外，算法处理速度能达到实时。这些结果证明了文中方法的有效性和优越性。

Abstract

A new aircraft attitude estimation algorithm by use of line features for multi-camera images was proposed based on the direction vector method of angle bisector line. First

the angle bisector method was used to get direction vectors of the central and coplanar vertical axes of the aircraft

thus the rotation matrix R from the aircraft coordinate system to the theodolite camera reference coordinate system was obtained. Then

all line edges of the wings on theodolite images were extracted

and the total spacial coplanar error equation functions of line characteristics were derived with the pitch

azimuth and other parameters of theodolite. Moreover

an improved orthogonal iteration method was presented to minimize the total error of rotation matrix R. Finally

the optimized rotation matrix R was decomposed to get the aircraft's attitude. By a simulation experiment

the accuracy of four-camera system achieves 0.17 and the speed is 32 frame/s

which shows the accuracy is much better than that of the angle bisector method and the processing speed reaches real-time level. These results prove the effectiveness and superiority of the proposed algorithm.

关键词

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references

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