基于直线特征的有理函数模型定位精度改善方法

Refine Method of Positioning Accuracy of Rational Function Model Based on Straight Line Features

探讨了利用已知直线特征进行有理函数模型定位误差在物方进行补偿的方法.推导了在两种物方补偿模型(平移加主因子比例和一阶仿射变换模型)下,基于已知直线特征进行补偿模型参数解算的数学模型.给出了利用已知直线特征进行有理函数模型定位误差补偿的解算方案.实验表明:基于线特征的补偿方法是可行的,并且平移加主因子比例模型的精度好于基于控制点的方法,也好于一阶仿射变换模型的补偿效果;但对于一阶仿射变换模型,该方法的补偿效果要比基于控制点的方法差.

This paper presents a discussion on the method which refines the rational function model（RFM） based stereo positioning in object space based on known straight line features. For the two refine models （the sshift and main factor model and the affine model）, the formulas were derivated to solve the refine model parameters based on known straight line features. And the solution using known straight linefeatures was given to compensate the RFM positioning error. The experimental results show that it is feasible to refine the RFM-based stereo positioning based on line features. In terms of compensation effect, shift and main factor model using the straight line features is better than both the shift and main factor models using points and the affine model, and the affine model using straight line features is worse than that using points.