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兵工学报 ›› 2013, Vol. 34 ›› Issue (3): 361-364.doi: 10.3969/j.issn.1000-1093.2013.03.016

• 研究论文 • 上一篇    下一篇

摄像机参数与地面点坐标改正数的分离估计

余家祥1, 赵晓哲1, 梁德清1, 姜鲁东2, 周晶v   

  1. 1. 海军大连舰艇学院战术学博士后流动站, 辽宁大连116018; 2. 海军装备部, 北京100083
  • 上线日期:2013-07-23
  • 作者简介:余家祥(1974—),男,副教授,博士。
  • 基金资助:

    中国博士后科学基金项目(2012M521893)

Separate Estimation for Corrections of Camera Parameters and Coordinates of Ground Points

YU Jia-xiang1, ZHAO Xiao-zhe1, LIANG De-qing1, JIANG Lu-dong2, ZHOU Jingv   

  1. 1. Arms Tactics Postdoctoral Mobile Station, Dalian Naval Academy, Dalian 116018, Liaoning, China; 2. Materiel Department, PLA Navy, Beijing 100083, China
  • Online:2013-07-23

摘要:

在基于多帧航空图像同名点的对地定位方法中,求解摄像机参数改正数和地面点坐标 改正数的一次完成最小二乘算法(LMS)的运算效率随同名点数目的增加而急剧下降。为解决该问 题,根据改正数约束方程中摄像机参数改正数系数矩阵与地面点坐标改正数系数矩阵相互独立的 特点,提出了摄像机参数改正数和地面点坐标改正数的分离估计新算法。该算法以分离LMS 为基 础,用迭代方法交替求解摄像机参数改正数和地面点坐标改正数。每一步迭代计算均按分块方式 处理系数矩阵,降低了系数矩阵维数,为改正数解算效率的提高创造了条件。仿真分析结果表明, 在保证改正数计算精度的同时,分离估计算法的运算效率优于一次完成算法。

关键词: 摄影测量与遥感技术, 摄像机参数, 地面点坐标, 改正数, 分离最小二乘法

Abstract:

In the geo-location method based on common points in multiple aerial images, the computa- tional efficiency of the simultaneous least square estimate used to reckon the corrections of aerial camera parameters and ground point coordinates degrades rapidly with the increase of the number of common points. To solve this problem, a novel algorithm is presented to separately estimate the corrections of camera parameters and ground point coordinates by considering the feature that the coefficient matrices of the corrections of camera parameters and ground point coordinates are independent. It is theoretically based on the separate least square estimation, and calculates the corrections of camera parameters and ground point coordinates in every iteration step alternately. In the iteration procedure, the coefficient ma- trices are parted to decrease their dimension numbers. Such partition improves the efficiency of correction computation. Simulation results show that the separate algorithm has higher computational efficiency than the present simultaneous algorithm, without degrading the precision of the corrections.

Key words: photogrammetry and remote sensing, camera parameter, ground point coordinate, correc- tion, separate least square

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