A Hybrid Conjugate Gradient Algorithm for Solving Relative Orientation of Big Rotation Angle Stereo Pair  

作　　者：Jiatian LI Congcong WANG Chenglin JIA Yiru NIU Yu WANG Wenjing ZHANG Huajing WU Jian LI 

机构地区：[1]Faculty of Land Resource Engineering,Kunming University of Science and Technology,Kunming 650093,China [2]Surveying and Mapping Geo-Informatics Technology Research Center,Plateau Mountains of Yunnan Higher Education of Kunming University of Science and Technology,Kunming 650093,China

出　　处：《Journal of Geodesy and Geoinformation Science》2020年第2期62-70,共9页测绘学报（英文版）

基　　金：National Natural Science Foundation of China(Nos.41561082;41161061)。

摘　　要：The fast convergence without initial value dependence is the key to solving large angle relative orientation.Therefore,a hybrid conjugate gradient algorithm is proposed in this paper.The concrete process is:①stochastic hill climbing(SHC)algorithm is used to make a random disturbance to the given initial value of the relative orientation element,and the new value to guarantee the optimization direction is generated.②In local optimization,a super-linear convergent conjugate gradient method is used to replace the steepest descent method in relative orientation to improve its convergence rate.③The global convergence condition is that the calculation error is less than the prescribed limit error.The comparison experiment shows that the method proposed in this paper is independent of the initial value,and has higher accuracy and fewer iterations.

关 键 词：relative orientation big rotation angle global convergence stochastic hill climbing conjugate gradient algorithm 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]