基于光流法地形跟随的矿区复杂地形无人机摄影测量
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摘要
受开采沉陷或地表资源剥离的影响,矿区地形一般较为复杂。传统摄影测量作业时根据矿区平均高程和测量精度要求,设计一个固定航高,按照该高度进行无人机影像采集。该方法因受地形起伏的影响,测区内摄影比例尺、影像重叠度、分辨率相差较大,导致测量精度不一致,甚至无法构成立体视觉条件,导致空三加密失败。为克服传统方法的不足,在分析地形起伏对测量精度影响的基础上,基于地形跟随技术,采用轻小型机器视觉模块,通过设计开发基于拓扑约束的快速光流估计算法,实时估计无人机相对地面的航高,并根据地形变化调整无人机飞行高度,实现实时地形跟随的矿区复杂地形摄影测量,从而保证在矿区复杂地形条件下摄影比例尺、影像重叠度、分辨率一致,满足精度均匀的摄影测量条件。研究表明:在矿区复杂地形条件下,能够达到1∶500大比例尺矿区地形图测绘精度要求,证明了该方法的有效性。
Affected by mining subsidence or surface resources stripping,the terrain of mining area is generally complex.In the traditional photogrammetry,a fixed aerial height is designed according to the requirements of average terrain and precision in the mining area,and UAV(Unmanned aerial vehicle)image collection is carried out according to this height. Due to the influence of topographic fluctuation,the photographic scale,image overlap degree and resolution difference in the measurement area are large,resulting in inconsistent measurement accuracy,even can not constitute stereoscopic visual conditions,air triangulation encryption failure.In order to overcome the shortcomings of traditional methods,on the basis of analyzing the influence of topographic relief on measuring accuracy,combing with the terrain following technique,the light and small machine vision module is adopted,the relative altitude of the UAV in real time can be estimated through developing the fast optical flow estimation algorithm based on topology constraints,besides that,the UAV flying height can be adjusted based on the changes of terrain,so as to realize the photogrammetry method of complex terrain in mining areas with real-time terrain tracking.In this way,the uniform photographic scale,image overlap and resolution can be guaranteed under the complex terrain conditions of the mining area,and the uniform photogrammetry can meet the requirements of expected accuracy.The study results show that the accuracy of 1∶500 large scale topographic map can be achieved in the complex terrain of mining area,which proves the effectiveness of the method.
Affected by mining subsidence or surface resources stripping,the terrain of mining area is generally complex.In the traditional photogrammetry,a fixed aerial height is designed according to the requirements of average terrain and precision in the mining area,and UAV(Unmanned aerial vehicle)image collection is carried out according to this height. Due to the influence of topographic fluctuation,the photographic scale,image overlap degree and resolution difference in the measurement area are large,resulting in inconsistent measurement accuracy,even can not constitute stereoscopic visual conditions,air triangulation encryption failure.In order to overcome the shortcomings of traditional methods,on the basis of analyzing the influence of topographic relief on measuring accuracy,combing with the terrain following technique,the light and small machine vision module is adopted,the relative altitude of the UAV in real time can be estimated through developing the fast optical flow estimation algorithm based on topology constraints,besides that,the UAV flying height can be adjusted based on the changes of terrain,so as to realize the photogrammetry method of complex terrain in mining areas with real-time terrain tracking.In this way,the uniform photographic scale,image overlap and resolution can be guaranteed under the complex terrain conditions of the mining area,and the uniform photogrammetry can meet the requirements of expected accuracy.The study results show that the accuracy of 1∶500 large scale topographic map can be achieved in the complex terrain of mining area,which proves the effectiveness of the method.
引文
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[21]杨盛伟,赵伟,刘建业.用于无人机导航的光流测速优化方法[J].电光与控制,2019,26(1):8-11.Yan Shengwei,Zhao Wei,Liu Jianye.An optimization method of optical flow velocimetry for UAV navigation[J].Electronics Optics&Control,2019,26(1):8-11.
[2]王峥羽,王文成.基于无人机倾斜摄影实景三维模型在矿山地形测量中的应用[J].矿山测量,2019,47(1):57-60.Wang Zhengyu,Wang Wencheng.Application of real scene 3D model based on UAV tilting photography in mine topography[J].Mine Surveying,2019,47(1):57-60.
[3]孟庆鹏,孙斌,凌清.天狼星无人机大比例尺测图精度分析[J].测绘通报,2018(3):158-161.Meng Qingpeng,Sun Bin,Ling Qing.Precision analysis of the large scale mapping based on sirius UAV[J].Bulletin of Surveying and Mapping,2018(3):158-161.
[4]侯树慧,李杰,牟冬星,等.旋翼无人机大比例尺测图应用及精度分析[J].城市勘测,2018(5):80-82.Hou Shuhui,Li Jie,Mu Dongxing,et al.Application and precision analysis of large-scale topographic survey using rotor UAV based on oblique photogrammetry[J].Urban Geotechnical Investigation&Surveying,2018(5):80-82.
[5]万剑华,王朝,刘善伟,等.消费级无人机的大比例尺测图能力分析[J].测绘通报,2018(6):104-108.Wan Jianhua,Wang Zhao,Liu Shanwei,et al.Analysis of large scale mapping capability of consumer unmanned aerial vehicles[J].Bulletin of Surveying and Mapping,2018(6):104-108.
[6]Gao Ning.High-precision and light-small oblique photogrammetry UAV landscape restoration monitoring[C]//9thInternational Conference on Intelligent Control and Information Processing,ICICIP2018:301-304.
[7]周小杰,胡振彪,乔新.无人机倾斜摄影技术在大比例尺地形图测绘中的应用[J].城市勘测,2019(1):63-66.Zhou Xiaojie,Hu Zhenbiao,Qiao Xin.The application of unmanned aerial vehicle oblique photography technique in large scale topographic mapping[J].Urban Geotechnical Investigation&Surveying,2019(1):63-66.
[8]Dewez,T J B.Reconstructing 3D coastal cliffs from airborne oblique photographs without ground control points[J].ISPRS Annals of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2014,2(5):113-116.
[9]李天.基于RTK技术的无人机在大比例尺地形图测绘中的精度分析[J].测绘与空间地理信息,2019,42(3):166-168.Li Tian.Precision analysis of UAV based on RTK/PPK technology in large scale topographic mapping[J].Geomatics&Spatial Information Technology,2019,42(3):166-168.
[10]张永年,李秀丽.地形起伏对无人机低空航测影响分析--以东桥镇、龙海市为例[J].测绘与空间地理信息,2013,36(3):176-178.Zhang Yongnian,Li Xiuli.The impact analysis of topographic relief for UAV low altitude aerial survey:taking Dongqiao Town,Longhai City as an Example[J].Geomatics&Spatial Information Technology,2013,36(3):176-178.
[11]王刚.无人机摄影测量用于大比例尺金属矿区测绘的实践探讨[J].世界有色金属,2017(9):150.Wang Gang.Practice of unmanned aerial vehicle photogrammetry in surveying and mapping large scale metal mines[J].World Nonferrous Metals,2017(9):150.
[12]马海鹏.无人机航摄系统快速测绘矿区大比例尺地形图的分析[J].世界有色金属,2017(14):49.Ma Haipeng.Analysis of large scale topographic map of rapid surveying and mapping mine area by unmanned aerial vehicle aerial photograph system[J].World Nonferrous Metals,2017(14):49.
[13]李涛.天狼星无人机航摄系统在复杂地形测量中的应用与精度分析[J].测绘通报,2017(12):146-148.Li Tao.Application and accuracy analysis of sirius UAV aerial photography system in complex topographic survey[J].Bulletin of Surveying and Mapping,2017(12):146-148.
[14]赵小勇,杨恒辉.一种新的地形跟随飞行方法与关键技术研究[J].计算机测量与控制,2012,20(7):1983-1986.Zhao Xiaoyong,Yang Henghui.Study on key techniques of a new approach to terrain-following flight[J].Computer Measurement&Control,2012,20(7):1983-1986.
[15]杨新勇,鲁艺.基于图像分割算法的地形跟随航路规划[J].弹箭与制导学报,2009,29(1):85-87.Yang Xinyong,Lu Yi.Study on path planning of terrain-following based on image segmentation[J].Journal of Projectiles,Rockets,Missiles and Guidance,2009,29(1):85-87.
[16]雍歧卫,喻言家,陈雁,等.地面管道无人机巡查起伏地形跟随方法[J].重庆理工大学学报:自然科学版,2017,31(8):158-162.Yong Qiwei,Yu Yanjia,Chen Yan,et al.Research on unmanned aerial vehicle pipeline tracking method[J].Journal of Chongqing University of Technology:Natural Science Edition,2017,31(8):158-162.
[17]魏东辉,陈万春,程进.无人飞行器基于前视序列图像的地形跟随技术[J].红外与激光工程,2017,46(4):1-7.Wei Donghui,Chen Wanchun,Cheng Jin.Terrain following based on forward-looking image sequences for unmanned air vehicles[J].Infrared and Laser Engineering,2017,46(4):1-7.
[18]牛渊.多传感器融合的小型无人机地形跟随系统设计[D].深圳:深圳大学,2017.Niu Yuan.The Design of Terrain Following System for UAV Based on Multiple Sensor Information Fusion[D].Shenzhen:Shenzhen University,2017.
[19]Livshitz,Arseny.Low-cost laser range-measurement-based terrainfollowing concept and error analysis[J].Journal of Guidance,Control and Dynamics,2018,41(4):1000-1008.
[20]刘小明,陈万春,邢晓岚,等.光流控制地形跟随与自动着陆[J].北京航空航天大学学报,2012,38(1):98-105.Liu Xiaoming,Chen Wanchun,Xing Xiaolan,et al.Terrain following and autonomous landing using optical flow[J].Journal of Beijing University of Aeronautics Astronautics,2012,38(1):98-105.
[21]杨盛伟,赵伟,刘建业.用于无人机导航的光流测速优化方法[J].电光与控制,2019,26(1):8-11.Yan Shengwei,Zhao Wei,Liu Jianye.An optimization method of optical flow velocimetry for UAV navigation[J].Electronics Optics&Control,2019,26(1):8-11.
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