利用RANSAC算法筛选坐标转换中相对稳定公共点

Relatively Stable Common Point Sift in Coordinate Transformation Using RANSAC Algorithm

为提高坐标转换的精度及可靠性,提出一种基于RANSAC算法的相对稳定公共点筛选方法。以四元数坐标转换模型为基础,引入RANSAC算法来迭代筛选控制网中相对稳定点,并将其作为公共点进行坐标转换,以提高转换精度。以加速器工程隧道控制网为例,对该方法进行仿真实验与分析,并与基于M估计的坐标转换结果进行对比。实验结果表明,所提方法能够精确定位粗差,相对稳定点误判率低于M估计结果,且坐标转换精度更高。

In order to improve the accuracy and reliability of coordinate transformation, a relatively stable common point sift method based on RANSAC algorithm is proposed. Based on quaternion coordinate transformation model, RANSAC algorithm is introduced to iteratively sift the relatively stable point in the control network and convert them into coordinates as common points, so as to improve the conversion accuracy. Taking the accelerator engineering tunnel control network as an example, simulation experiments and case analysis are carried out, and the results are compared with the result of coordinate transformation based on M estimation. The results show that this method can accurately locate the gross error, the misjudgment rate of the relatively stable point is lower than the result of M-estimation, and its coordinate conversion accuracy is higher.