几何约束自检校的无人机高精度影像定向与纠正算法研究

项目名称： 几何约束自检校的无人机高精度影像定向与纠正算法研究

项目编号： No.41271395

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 天文学、地球科学

项目作者： 谢文寒

作者单位： 中国测绘科学研究院

项目金额： 60万元

中文摘要： 近年来，低空遥感技术受到众多应用领域的高度关注。其中，光学传感器由以往的可量测型专业相机逐渐被非量测相机所替代。和卫星遥感影像、传统航空遥感影像相比，低空无人机光学遥感影像具有低成本、高分辨率、地面特征丰富、应用灵活等特点。但影像的稳定性受飞行器的姿态变化影响较大，难以进行高精度的影像定向。本项目以无人机为数据获取平台，针对城市区域大比例尺低空影像的特点，提出一种基于未标定相机的高精度UAV影像定向及几何纠正方法，该方法在广义点（灭点）理论的支持下，研究基于线特征IAC约束的的影像精确定位、定向算法，以及三步分解法的模型误差传播与精度分析。同时，充分利用低空影像中建筑物目标的线特征，采用基于广义点几何约束的区域网平差算法对几何纠正进行精度改进。通过实验分析，得到低空影像区域网平差的精度分析报告，实现UAV影像定向参数与纠正算法的优化。

中文关键词： UAV；相机定标；影像定向；几何约束；平差模型

英文摘要： Recent years, a number of types of UAV(Unmanned aerial vehicle) systems with various onboard sensors have been developed for civilian applications such as homeland security, urban and city planning, forestry fire monitoring, quick response measurements for emergency disaster, Earth science research, and humanitarian observations. Recent developments in the vehicles themselves and associated sensing systems make these platforms increasingly attractive to the geoscience community. UAV platforms and imaging and sensing systems that are adaptable to these platforms facilitate unique capabilities in Earth observation for both research and operational monitoring purposes. Compared with traditional satellite and aerial remote sensing images, UAV image has the features of lower cost, high resolution and quick response. However, its stabilization may be affected dramatically by the light weight of the vehicle, so it's difficult to take the image orientation with high accuracy. Focusing on the features of urban area large-scale UAV image, this project proposes uncalibrated camera based method of high accurate UAV image orientation and geometric rectification. With the theory of generalized point photogrammetry, the project develops IAC (Image of Absolute Conic) based image calibration and orientation algorithm, and also

英文关键词： UAV；camera calibration；image orietation；geometry constraint；bundle adjustment