Ground target localization method combining unmanned aerial vehicle pose information

doi:10.13474/j.cnki.11-2246.2025.0804

Abstract

Abstract: Traditional methods for ground target localization using single-frame drone images typically require at least four prior control point information.However,acquiring control points becomes increasingly challenging as their quantity increases,presenting an arithmetic growth problem.This paper proposes a ground target localization method that integrates unmanned aerial vehicle(UAV)pose information.The method combines UAV pose information with three ground control points to establish a geometric optical model.This model enables the mapping relationship between ground target points and UAV image pixels,facilitating the determination of latitude and longitude coordinates for each ground target point.Consequently,precise ground target localization based on a single-frame drone image is achieved,reducing the required number of control points and enhancing localization accuracy.The experimental results indicate that the average positioning accuracy of this method reaches 1.45 pixels,which is 4.61 pixels higher than that of the traditional PnP four-point target positioning method.

Key words: ground target positioning, UAV, position and attitude information, control points, geometric optical model

CLC Number:

LUO Qingli, ZHANG Shubin, JIANG Xintao, WEI Jujie, GAN Jun. Ground target localization method combining unmanned aerial vehicle pose information[J]. Bulletin of Surveying and Mapping, 2025, 0(8): 19-25.

References

[1] PEI Xinhao,JIA Shengde,ZHU Huayong.Targets assinment for multi-UCAV cooperative using a game theroy approach[C]//Proceedings of the 2nd International Conference on Computer Science and Network Technology.Changchun: IEEE,2012:793-797.
[2] 刘钢,廖守亿,于功健,等.时敏目标打击作战信息链仿真研究[J].信息通信,2016,29(10):76-79.
[3] HASSANALIAN M,ABDELKEFI A.Classifications,applications,and design challenges of drones:a review[J].Progress in Aerospace Sciences,2017,91:99-131.
[4] 钟麟,张岐坦.基于无人机载光电平台的目标定位技术[J].计算机与网络,2021,47(13):53-57.
[5] 刘晶红,沈宏海,孙树红,等.机载光电成像平台的目标自主定位[J].光机电信息,2008,25(1):24-28.
[6] YU J X,XIAO D Y,JIANG L D,et al.Approach for geo-location with unmanned aerial vehicle[J].Opto-Electronic Engineering,2007,34(7):1-7.
[7] FISCHLER M A,BOLLES R C.Random sample consensus:a paradigm for model fitting with applications to image analysis and automated cartography[J].Readings in Computer Vision,1987,24(6):726-740.
[8] 白冠冰,宋悦铭,左羽佳,等.机载光电平台的对地多目标定位[J].光学精密工程,2020,28(10):2323-2336.
[9] WU W T.Basic principles of mechanical theorem proving in elementary geometries[J].Journal of Automated Reasoning,1986,2(3):221-252.
[10] LEPETIT V,MORENO-NOGUER F,FUA P.EPnP:an accurate O(n)solution to the PnP problem[J].International Journal of Computer Vision,2009,81(2):155-166.
[11] 周润,张征宇,黄叙辉.相机位姿估计的加权正交迭代算法[J].光学学报,2018,38(5):193-199.
[12] 孙贵新,王东亮,李琦,等.一种无人机相机结合靶标的定位方法[J].指挥控制与仿真,2023,45(2):1-8.
[13] 马振华,张鹏飞,何印,等.基于UWB辅助的多无人机惯导定位误差校正方法[J].计算机测量与控制,2023,31(9):253-259.
[14] 王继红,吴伯彪,张亚超,等.视觉和惯导信息融合小型无人机位姿估计研究[J].中国测试,2021,47(11):134-140.

[1]	YIN Junjie, GUAN Daiwanjing, LI Hao, ZHANG Xiaoyang, MA Yujie, XING Hanfa. UAV-based object recognition dataset for coastal sewage outfalls [J]. Bulletin of Surveying and Mapping, 2025, 0(8): 112-117.
[2]	ZHANG Yongli, ZHU Wenchao, FAN Yewen, QU Zhi. GNSS-assisted UAV aerial photography technology for obtaining data for quality inspection of new surveying and mapping products [J]. Bulletin of Surveying and Mapping, 2025, 0(8): 153-158.
[3]	HU Yaofeng, CHENG Xiangbing, CHEN Jiaqi. Urban multi-dimensional sensing infrastructure: architectural innovations and monitoring applications [J]. Bulletin of Surveying and Mapping, 2025, 0(8): 174-178.
[4]	GUO Zhendong, WU Hao, GU Zhengdong, HUANG Liang. Real-scene 3D data acquisition and fusion technologies inside and outside caves:take Yixing Shanjuan Cave for an example [J]. Bulletin of Surveying and Mapping, 2025, 0(8): 149-152.
[5]	CHEN Chao, ADILI Rusuli, LI Xiaojun, RUI Yi, LV Yanyun, LU Linhai. Dynamic feedback method for slope construction based on UAV and digital twin [J]. Bulletin of Surveying and Mapping, 2025, 0(5): 131-137.
[6]	CHEN Fuqiang, WEI Yujun, MA Bangchuang, LI Dan, LIU Yuxin, ZHANG Zhanzhong. Application of UAV aerial survey and remote sensing technology in the improvement and renovation of existing railways: taking the Baotian section of the Longhai Railway as an example [J]. Bulletin of Surveying and Mapping, 2025, 0(4): 158-163.
[7]	YANG Jiafang, YIN Linjiang, ZHANG Hongliang, ZHAO Weiquan, LI Wei. The extraction method of tea plantation information based on multi-dimensional features from UAV remote sensing images [J]. Bulletin of Surveying and Mapping, 2025, 0(3): 138-143.
[8]	YU Wei, LIU Mincong, WANG Meng, LIU Yue, LI Jikun, YANG Jie, LI Tuanjie. Application of UAV photogrammetry in the survey of sandy coast ecosystem [J]. Bulletin of Surveying and Mapping, 2025, 0(3): 144-149.
[9]	ZHONG Weihua, LIU Jingkuang. Dynamic monitoring for open-pit mine reclamation based on UAV oblique photogrammetry [J]. Bulletin of Surveying and Mapping, 2025, 0(3): 21-26.
[10]	CHENG Jie, ZHONG Yong, YANG Yugang, JIAO Baotong, ZHANG Fusheng. Design and implementation of an intelligent yard management platform based on UAV: a case study of Rizhao port [J]. Bulletin of Surveying and Mapping, 2025, 0(3): 178-182.
[11]	XIANG Tao, XU Zhangping, MA Weili, CHU Fuyu, GUO Shengnan, HE Minggang, DONG Kang, ZHENG Zumei. Application of UAV and unmanned ships in the review of reservoir capacity curves [J]. Bulletin of Surveying and Mapping, 2025, 0(2): 156-162.
[12]	ZHANG Yongting, LIN Jiangtao, XIE Shaomin, LIU Jian. Super-resolution reconstruction of aerial images from self-supervised UAV based on non-local mining reconstruction network [J]. Bulletin of Surveying and Mapping, 2025, 0(1): 16-21.
[13]	WEI Zhongyang, HUANG Jingjin, GUO Weili, FENG Yijun, LI Zhenghong, WEI Qiulian, PAN Yifeng, XIE Hong. Research and practice of UAV network monitoring for cultivated land change [J]. Bulletin of Surveying and Mapping, 2024, 0(9): 140-144.
[14]	LAN Guiwen, XU Zirui, REN Xinyue, ZHONG Zhan, GUO Ruidong, FAN Donglin. An improved algorithm for detecting components of power transmission lines from aerial inspection images [J]. Bulletin of Surveying and Mapping, 2024, 0(9): 38-43,49.
[15]	XU Yuxiang, HU Qingwu, DUAN Yansong, LI Jiayuan, AI Mingyao, ZHAO Pengcheng. Landslide dynamic monitoring technology by integrating LiDAR point cloud and UAV image [J]. Bulletin of Surveying and Mapping, 2024, 0(8): 42-47.