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应用科学学报 ›› 2012, Vol. 30 ›› Issue (2): 209-214.doi: 10.3969/j.issn.0255-8297.2012.02.016

• 论文 • 上一篇    下一篇

机器视觉辅助的无人机空中加油相对导航

王龙1， 董新民1， 贾海燕2   

  1. 1. 空军工程大学工程学院，西安710038
    2. 中国人民解放军93942部队，陕西咸阳712000  
  • 收稿日期:2011-03-13 修回日期:2011-07-04 出版日期:2012-03-26 发布日期:2012-03-30
  • 通信作者: 王龙，博士生，研究方向：自主空中加油视觉相对导航、组合导航、数据融合等，E-mail: afeu78@126.com；
  • 作者简介:王龙，博士生，研究方向：自主空中加油视觉相对导航、组合导航、数据融合等，E-mail: afeu78@126.com；董新民，教授，博导，研究方向：飞行器控制理论与应用、智能控制等，E-mail: dongxinmin@163.com
  • 基金资助:

    航空科学基金(No.2008ZC01006)资助

Machine Vision-Aided Relative Navigation for UAV Aerial Refueling

WANG Long1, DONG Xin-min1, JIA Hai-yan2     

  1. 1. College of Engineering, Air Force Engineering University, Xi’an 710038, China
    2. Unit 93942, People’s Liberation Army, Xianyang 712000, Shaanxi Province, China
  • Received:2011-03-13 Revised:2011-07-04 Online:2012-03-26 Published:2012-03-30

PDF

1511

被引次数

13

摘要：

为准确获取无人机空中加油对接阶段的相对位姿信息，提出了一种机器视觉辅助的INS/GPS/MV 组合导航方案，研究了机器视觉图像的特征点提取与匹配算法. 引入相对惯导误差，建立了全局滤波器的增广状态方程，并根据杆臂矢量推导了GPS和机器视觉量测方程. 设计了基于联邦滤波器结构的全局多速率扩展卡尔曼滤波算法，以融合多速率传感器信息，并与标准EKF算法进行对比. 仿真结果表明，所提出的算法能有效融合惯导、GPS和机器视觉的测量信息，使导航参数的精度和输出带宽均满足导航系统的设计要求，有利于改善无人机的飞行品质，放宽对飞控系统的性能要求.

关键词: 机器视觉, 空中加油, 相对导航, 扩展卡尔曼滤波

Abstract:

To precisely obtain the relative pose of UAV during aerial refueling docking, a machine vision-aided INS/GPS/MV integrated navigation scheme is proposed. Feature extraction and match algorithm of machine vision image are studied. By introducing relative inertial errors, an extended state model of global filter is designed. GPS and machine vision measurement models are established using level-arm vectors. A global multirate extended Kalman filter based on federal framework is designed to realize multirate mutisensor data fusion. Comparison is made between the proposed algorithm and the standard EKF algorithm. Simulation shows that the proposed algorithm can effectively fuse INS/GPS/MV data. The navigation parameter precision and output bandwidth satisfy the requirements of UAV aerial refueling. It can improve UAV qualities and loosen requirements of flight control systems.

Key words: machine vision, aerial refueling, relative navigation, extended Kalman filter

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