测绘学报 ›› 2017, Vol. 46 ›› Issue (5): 593-604.doi: 10.11947/j.AGCS.2017.20160081

• 摄影测量学与遥感 • 上一篇    下一篇

多像空间前方交会的抗差总体最小二乘估计

李忠美1, 边少锋1, 瞿勇2   

  1. 1. 海军工程大学导航工程系, 湖北 武汉 430033;
    2. 海军工程大学理学院, 湖北 武汉 430033
  • 收稿日期:2016-02-29 修回日期:2017-02-22 出版日期:2017-06-20 发布日期:2017-06-05
  • 通讯作者: 边少锋 E-mail:sfbian@sina.com
  • 作者简介:李忠美(1990-),女,博士生,研究方向为摄影测量理论算法。E-mail:15827116839@163.com
  • 基金资助:
    国家自然科学基金(41631072;41471387;41604010)

Robust Total Least Squares Estimation of Space Intersection Appropriate for Multi-images

LI Zhongmei1, BIAN Shaofeng1, QU Yong2   

  1. 1. Department of Navigation, Naval University of Engineering, Wuhan 430033, China;
    2. College of Science, Naval University of Engineering, Wuhan 430033, China
  • Received:2016-02-29 Revised:2017-02-22 Online:2017-06-20 Published:2017-06-05
  • Supported by:
    The National Natural Science Foundation of China (Nos. 41631072;41471387;41604010)

摘要: 为充分利用现有观测数据来确定地面点位置,根据立体像对的前方交会原理,通过建立目标点到多条同名射线距离的加权平方和作为目标函数,对其求一阶和二阶导数,得到多像空间前方交会的抗差总体最小二乘估计。相对于立体像对,多张像片的空间前方交会方法可利用更多的观测信息并引入了稳健估计理论,具有更高的交会精度及稳健性能。最后,通过算例验证了该方法的正确性与稳健性,可一定程度上丰富摄影测量空间前方交会理论。

关键词: 摄影测量, 多张像片, 前方交会, 空间距离, 总体最小二乘法, 选权迭代法

Abstract: In order to take full advantage of available observation resources, based on theory of space intersection with stereo images, by conducting weighted quadratic sum of spatial distance from the target point to multiple space lines as the objective function and carrying out its first as well as second derivatives, robust total least squares estimation of space intersection appropriate for multi-images was realized. Compared to stereopair, more observed information and theories of robust estimation were considered in the process of space intersection with multi-images, bringing about higher intersection accuracy and robustness. Finally, correctness and robustness of the method was verified though example analysis, which can enrich the space intersection theory in photogrammetry to some degree.

Key words: photogrammetry, multi-images, space intersection, spatial distance, total least squares method, reweighting iteration method

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