引用本文: | 苏昂,雷志辉,张跃强,等.未知环境下飞行器视觉/惯导组合测速测高方法.[J].国防科技大学学报,2014,36(1):17-21.[点击复制] |
SU Ang,LEI Zhihui,ZHANG Yueqiang,et al.A velocity and height estimation method based on vision/inertial for aircraft in unknown environments[J].Journal of National University of Defense Technology,2014,36(1):17-21[点击复制] |
|
|
|
本文已被:浏览 9850次 下载 7009次 |
未知环境下飞行器视觉/惯导组合测速测高方法 |
苏昂1,2, 雷志辉1,2, 张跃强1,2, 朱宪伟1,2, 刘海波1,2 |
(1.国防科技大学 航天科学与工程学院,湖南 长沙 410073;2.
2.国防科技大学 图像测量与视觉导航湖南省重点实验室,湖南 长沙 410073)
|
摘要: |
针对未知环境下飞行器导航问题,提出一种基于视觉/惯导组合的测速测高方法。该方法构建包含前若干个成像时刻飞行器位置的惯导扩展状态方程,并采用一种基于摄像机两视图对极几何约束的线性视觉量测方程,通过卡尔曼滤波进行惯导速度修正,在此基础上利用多帧成像的立体视觉交会估计地面特征点坐标,进而得到飞行器相对高度。以飞行器典型巡航轨迹进行的仿真实验表明,该方法能够有效修正飞行器速度和相对高度误差,给出不随时间漂移的速度和相对高度测量结果,并很好地抑制飞行器位置误差的发散。 |
关键词: 视觉导航 惯性导航 速度测量 高度测量 卡尔曼滤波 |
DOI:10.11887/j.cn.201401004 |
投稿日期:2013-05-03 |
基金项目:国家自然科学基金资助项目(60904084);国家重点基础研究发展计划项目(2013CB733100) |
|
A velocity and height estimation method based on vision/inertial for aircraft in unknown environments |
SU Ang1,2, LEI Zhihui1,2, ZHANG Yueqiang1,2, ZHU Xianwei1,2, LIU Haibo1,2 |
(1.College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China;2.Hunan Key Laboratory of Videometrics and Vision Navigation, National University of Defense Technology, Changsha 410073, China)
|
Abstract: |
For aircraft navigation in unknown environments, a velocity and height estimation method based on vision/inertial integrated navigation is proposed. An extended inertial navigation state equation was formulated, which contains several aircraft’s positions at latest several imaging times, and a linear vision measurement equation based on two view epipolar geometry constraints was adapted to correct inertial velocity error using a Kalman filter. And then, the coordinates of ground features were estimated by the stereo vision method, which was used to estimate the height of the aircraft. Simulation has been implemented by using the typical cruise trajectory of the aircraft, and the result shows that our method works well for correcting the velocity and height errors, which enables the velocity and height not to drift with time. As a result, it can also suppress the position error of the aircraft. |
Keywords: vision navigation inertial navigation velocity measurement height measurement Kalman filter |
|
|
|
|
|