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遥感技术与应用  2014, Vol. 29 Issue (3): 506-510    DOI: 10.11873/j.issn.1004-0323.2014.3.0506
图像与数据处理     
一种求解无人机影像外方位角元素的方法
李政,李永树,唐敏
(西南交通大学地理信息工程中心,四川 成都610031)
A Method of Directly Calculating UAV Exterior Azimuth Elements
Li Zheng,Li Yongshu,Tang Min
(GIS engineering Center of Southwest Jiaotong University,Chengdu 610031,China)
 全文: PDF(2852 KB)  
摘要:

针对无人机本身质量轻、荷载低,自带的POS数据精度不高,原始影像外方位元素不准且很难估算等问题,提出了一种基于线性变换的非迭代算法求解无人机外方位角元素的方法。该方法无需进行最小二乘迭代就可以直接计算出外方位角元素,且所求出的外方位角元素精度较高,可以对POS数据进行一定的修正,且修正之后POS数据精度有了较大的改善。实验结果表明:该方法所求得的外方位元素可以作为后续影像匹配、相对定向的初始值,能够在一定程度上满足无人机影像分析应用需求。

关键词: POS数据共线方程外方位角元素无人机影像    
Abstract:

Because the UAV(Unmanned Aerial Vehicle) is light\|weighted,low\|loaded and the accuracy of its own build\|in POS data measuring instrument is not high,and the original image of the exterior orientation element is not only inaccurate,but also difficult to estimate,this paper based on the non-iterative solution of linear transformation, proposes a method of calculating UAV exterior azimuth elements that can calculate the exterior azimuth elements directly without the traditional Least\|squares Iterative Method.The accuracy of the exterior orientation elements obtained by this method is higher,and the obtained elements can revise the data of the POS at the same time.Compared with the coordinate precision of ground test point calculated by the original data,the POS data has been greatly improved.The result shows that the acquired exterior azimuth elements can be more definitely used as the initial value of the subsequent image matched,relative orientation to meet the application demands of UAV image analysis.
 

Key words: Positioning and Orientation System(POS)    The collinearity equations    Exterior azimuth elements    UAV image
收稿日期: 2013-04-25 出版日期: 2014-06-23
:  TP 75  
作者简介: 李政(1989-),男,河北邯郸人,硕士研究生,主要从事3S技术与系统集成研究。Email:601250819@qq.com。
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引用本文:

李政,李永树,唐敏. 一种求解无人机影像外方位角元素的方法[J]. 遥感技术与应用, 2014, 29(3): 506-510.

Li Zheng,Li Yongshu,Tang Min. A Method of Directly Calculating UAV Exterior Azimuth Elements. Remote Sensing Technology and Application, 2014, 29(3): 506-510.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2014.3.0506        http://www.rsta.ac.cn/CN/Y2014/V29/I3/506

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