基于RANSAC的坐标系转换抗差算法研究

刘猛奎; 赵明金; 石波; 王云鹏; 张倩

doi:DOI:10.13442/j.gnss.1008-9268.2019.01.006

基于RANSAC的坐标系转换抗差算法研究

doi: DOI:10.13442/j.gnss.1008-9268.2019.01.006

刘猛奎¹,
赵明金²,
石波^1,,
王云鹏¹,
张倩^1

1.
山东科技大学测绘科学与工程学院,山东青岛 266590
2.
山东省国土测绘院,山东济南 250102

详细信息

作者简介:
石波 (1979-),男,博士,副教授,主要从事GNSS／INS组合导航和车载移动测量系统中多传感器集成及数据处理等方面的研究．

通讯作者:
石波 E-mail :shibo@sdust.edu.cn

计量
- 文章访问数: 515
- HTML全文浏览量: 55
- PDF下载量: 94
- 被引次数: 0
出版历程
- 刊出日期: 2019-02-15

Research on robust algorithm of coordinate system transformation based on RANSAC

2.
College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China

摘要

摘要: 空间坐标转换在大地测量、工程测量等领域应用广泛．在利用公共点求解坐标转换参数时,针对公共点中混有多粗差点的情形,给出了基于罗德里格矩阵的坐标系转换模型,并在此基础上提出了基于随机抽样一致性(RANSAC)算法粗差剔除的坐标系转换抗差估计．最后利用仿真数据对该算法进行了验证,同时将该抗差算法与基于IGG3方案的最小二乘抗差估计算法进行了比较．算例结果表明,在20个仿真公共点数据中(仿真多组数据),当粗差点个数超过公共点总数的3／10时,基于IGG3方案的最小二乘抗差算法失效,而基于RANSAC的抗差算法在粗差点个数达到公共点总数的1／2时,依然能保证坐标转换的精度．该抗差算法将RANSAC算法的思想应用到坐标系转换上,有效地剔除了公共点中混有的大量粗差点.
- 坐标系转换 /
- 抗差 /
- RANSAC /
- 罗德里格矩阵
Abstract: Space coordinate transformation is widely used in geodetic surveying and engineering surveying field. When using the common point to solve the coordinate transformation parameter, the coordinate system transformation model based on Rodriguez matrix was given and a coordinate transformation robust algorithm based on Random Sample consensus (RANSAC) was proposed for the problem of multiple rough points in the common point. At the same time, the algorithm was compared with the least squares robust algorithm based on IGG3 scheme. The results of the example show that when the rough points ratio exceeds 3／10 in the simulation of 20 common points(multiple sets of data), the least squares robust algorithm based on IGG3 scheme begins to fail, while the coordinates transformation robust algorithm based on RANSAC can also ensure the accuracy of coordinate transformation, even if the rough points ratio reached 1／2. The robust algorithm applies the idea of the RANSAC algorithm to the coordinate system transformation and effectively eliminates a large number of rough points that are mixed in common points.
- coordinate system transformation /
- robust /
- RANSAC /
- rodriguez matrix

HTML全文

参考文献(20)

[1]	於宗俦, 李明峰. 多维粗差的同时定位与定值［J］. 武汉测绘科技大学学报, 1996,21(4): 323-329.
[2]	KUBIK K. An error theory for the Danish method［C］// Symposium of ISP Comm.III, Helsinki, 1982.
[3]	周江文. 经典误差理论与抗差估计［J］. 测绘学报, 1989, 18(2): 116-120.
[4]	杨元喜, 宋力杰, 徐天河. 大地测量相关观测抗差估计理论［J］. 测绘学报, 2002, 31(2):95-99.
[5]	李德仁, 袁修孝. 误差处理与可靠性理论［M］. 武汉:武汉大学出版社, 2002.
[6]	吴祖海, 罗伟钊, 李军. 坐标转换中公共点粗差定位与降低粗差点影响［J］. 大地测量与地球动力学, 2014, 34(1): 118-122.
[7]	徐波, 高井祥, 李增科,等. 基于选权迭代的总体最小二乘算法在三维坐标转换中的应用［J］. 大地测量与地球动力学, 2015, 35(4):693-696.
[8]	张洋, 张志刚, 钱栋,等. 基于IGGIII模型的高精度抗差坐标转换算法研究［J］. 全球定位系统, 2017, 42(5):25-28.
[9]	倪飞. 几种抗差算法在坐标转换中应用的对比研究［J］. 矿山测量, 2017, 45(4):92-96,120.
[10]	GE Y, YUAN Y, JIA N. More efficient methods among commonly used robust estimation methods for GPS coordinate transformation［J］. Advanced Materials Research, 2013, 45(330):229-234.
[11]	GONG X, LI Z. A robust weighted total leastsquares solution with Lagrange multipliers［J］. Empire Survey Review, 2015, 49(354):176-185.
[12]	陈付幸, 王润生. 基于预检验的快速随机抽样一致性算法［J］. 软件学报, 2005, 16(8): 1431-1437.
[13]	RAGURAM R, FRAHM J M, POLLEFEYS M. A comparative analysis of RANSAC techniques leading to adaptive realtime random sample consensus［C］／／European Conference on Computer Vision. Springer, Berlin, Heidelberg, 2008:500-513.
[14]	卞玉霞, 刘学军, 刘丹. RANSAC估算基础矩阵的不确定性评价［J］. 地理与地理信息科学, 2015, 31(1): 37-40.
[15]	HOSSEINNEJAD Z, NASRI M. Image registration based on SIFT features and adaptive RANSAC transform［C］// International Conference on Communication and Signal Processing. IEEE, 2016.
[16]	LEE D, YOON J, LIM S. Image stitching using multiple homographies estimated by segmented regions for different parallaxes［C］／／International Conference on Vision, Image and Signal Processing. IEEE, 2017:71-75.
[17]	韩梦泽, 李克昭. 基于罗德里格矩阵的空间坐标转换［J］. 测绘工程, 2016, 25(4):25-27.
[18]	宋卫艳. RANSAC算法及其在遥感图像处理中的应用［D］. 北京: 华北电力大学, 2011.
[19]	FISCHLER M A, BOLLES R C. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography［J］. Readings in Computer Vision, 1987:726-740.
[20]	陈义, 陆珏. 以三维坐标转换为例解算稳健总体最小二乘方法［J］. 测绘学报, 2012, 41(5): 715-722.