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光电工程
第 34 卷第 7 期
100m CEP at best [4-5], which is inadequate for precision strike. Therefore, some new accurate UAV geo-location methods have been given in literatures [6-8].
Inspired by reference [11], this paper provided a new UAV geo-location method. In this method, at least three images of the target from nonlinear viewpoints, along with at least three identifiable common points among the images, will allow the calculation of the 3D coordinates of the target and all common points among the images. The new method doesn’t depend on DEM and the measured values of camera pose angles, therefore two of the three primary error sources in the traditional UAV target location are eliminated.
无人机对地成像定位方法
余家祥 1, 2，萧德云 1，姜鲁东 3，郭 锐 2
( 1. 清华大学 自动化系，北京 100084；2. 海军大连舰艇学院 舰载武器系，
辽宁 大连 116018；3. 海军驻西安地区舰炮军事代表室，陕西 西安 7100人机对地定位方法的精度不能满足精确打击作战需求的问题，本文提出一种
In reference[5], Gibbins, et al. use low-cost GPS, video and attitude sensors to estimate the position of ground targets. This method cannot work with a pan, tilt and zooming camera mount. Xie and Li[7] calculate geographical coordinates of a target by computing correlation between real time image and digital terrain map of local target area. His method has the accuracy of 50m CEP. Duan[8] presents a geo-location approach using sequential aerial images, which is similar to those used in references [9,10]. The approach is composed of two stages: relative position estimation and absolute position estimation. The former is based on stereo modeling of two successive image frames, whereas the latter is accomplished by matching the real-time images with reference images. The most serious shortcoming of Duan’s method is the inability to work without ground control points.
The rest of this paper is organized as follows. Section 2 gives the camera model described by collinearity equations. Section 3 expresses how to estimate the parameters of the camera. Then, in Section 4, the intersection for geo-location is presented. In Section 5, results of experiments on realization of the theory are shown, for both Monte Carlo simulation data and real aerial images. Section 6 presents some concluding remarks and ideas for future work.
传统无人机对地定位方法三个定位误差源中的两个，因此具有较高的定位精度。仿真与真实图像实验计算表明:
摄站本身坐标误差的大小是决定对地定位精度的主要因素，当采用 DGPS 定位摄站时，可以获得很高的目标定位
精度。
关键词：对地定位；同名点；数字高程模型；无人机
中图分类号：TP391.41，P234.4
文献标志码：A
第 34 卷第 7 期 2007 年 7 月
光电工程
Opto-Electronic Engineering
Vol.34, No.7 July, 2007
文章编号：1003-501X(2007)07-0001-07
Approach for Geo-location with unmanned aerial vehicle
新的无人机对地定位方法。该方法通过线性化共线条件方程建立摄像机姿态角和焦距迭代计算模型，根据非共线
位置拍摄的多帧图像及至少 3 个可识别同名像点坐标迭代计算摄像机姿态角和焦距的精确值，然后利用多摄站前
方交会法求取地面目标的三维坐标。该方法不依赖于数字高程模型(DEM)及像片内外方位元素的测量值，消除了
收稿日期：2006-12-18；收到修改稿日期：2007-05-28 基金项目：国防预研基金 作者简介：余家祥(1974-)，男(汉族)，安徽霍邱人，博士研究生，主要研究方向为军用无人机系统作战使用、特种弹技术及其作战使用、
图像处理等。E-mail: yujx03@
1 Camera model
In this paper, the pinhole camera model, i.e. the central projection model, is used as the projection model. We
denote the image taken from the ith viewpoint by Ii, and denote the jth point in the 3D world coordinate system
Abstract：The accuracy of traditional single image based on geo-location method using Unmanned Aerial Vehicle (UAV) is too low to meet the needs of precise strike. To solve the problem, a new UAV geo-location method is presented in this article. The mathematical models are constructed by linearizing the colinearity equations and iteratively computing the pose angles and focal length of the camera. At least three images of the target, along with at least three identifiable common points among the images, are needed for reckoning camera pose angles and focal length. The three dimensional (3D) coordinates of ground target are calculated using forward intersection. The new method can get the target coordinates without dependence on Digital Elevation Model (DEM). Measured values of camera pose angles are not used directly for geo-location. Two of the three primary error sources in the traditional UAV target location approach are eliminated. Simulation and real image experiment results show that the accuracy of the estimated target location is very high if the UAV is navigated by Differential Global Positioning Systems (DGPS). Key words：geo-location; common points; digital elevation model; unmanned aerial vehicle