A hybrid conjugate gradient algorithm for solving relative orientation of big rotation angle stereo pair

doi:10.11947/j.AGCS.2019.20170672

Abstract

Abstract: The fast convergence without initial value dependence is the key of large angle relative directional solution. Therefore, a hybrid conjugate gradient algorithm is proposed in this paper. The concrete process is:① stochastic hill climbing(SHC) algorithm is used to make random disturbance to the given initial value of the relative directional element, and the new value to guarantee the optimization direction is generated; ② In local optimization, super-linear convergent conjugate gradient method is used to replace the steepest descent method in relative orientation to improve its convergence rate; ③ The 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 initial value, has higher accuracy and fewer iterations.

Key words: relative orientation, big rotation angle, global convergence, stochastic hill climbing algorithm, conjugate gradient algorithm

CLC Number:

P237

LI Jiatian, WANG Congcong, JIA Chenglin, NIU Yiru, WANG Yu, ZHANG Wenjing, WU Huajing, LI Jian. A hybrid conjugate gradient algorithm for solving relative orientation of big rotation angle stereo pair[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(3): 322-329.

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