General Total Least Squares Theory for Geodetic Coordinate Transformations

被引:7
|
作者
Qin, Yuxin [1 ]
Fang, Xing [1 ]
Zeng, Wenxian [1 ]
Wang, Bin [2 ]
机构
[1] Wuhan Univ, Sch Geodesy & Geomat, Wuhan 430079, Peoples R China
[2] Nanjing Tech Univ, Coll Geomat Sci & Technol, Nanjing 211816, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2020年 / 10卷 / 07期
基金
中国国家自然科学基金;
关键词
total least squares; Gauss-Newton algorithm; errors-in-variables; affine; orthogonal; similarity; rigid transformations; constraints; general algorithm; AFFINE;
D O I
10.3390/app10072598
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Datum transformations are a fundamental issue in geodesy, Global Positioning System (GPS) science and technology, geographical information science (GIS), and other research fields. In this study, we establish a general total least squares (TLS) theory which allows the errors-in-variables model with different constraints to formulate all transformation models, including affine, orthogonal, similarity, and rigid transformations. Through the adaptation of the transformation models to the constrained TLS problem, the nonlinear constrained normal equation is analytically derived, and the transformation parameters can be iteratively estimated by fixed-point formulas. We also provide the statistical characteristics of the parameter estimator and the unit of precision of the control points. Two examples are given, as well as an analysis of the results on how the estimated quantities vary when the number of constraints becomes larger.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] Sterling interpolation method for precision estimation of total least squares
    Wang, Leyang
    Zhao, Yingwen
    Zou, Chuanyi
    Yu, Fengbin
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2023, 52 (01) : 142 - 160
  • [42] Total Least Squares Estimation in Hedonic House Price Models
    Zhan, Wenxi
    Hu, Yu
    Zeng, Wenxian
    Fang, Xing
    Kang, Xionghua
    Li, Dawei
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2024, 13 (05)
  • [43] Second-Order Approximation Function Method for Precision Estimation of Total Least Squares
    Wang, Leyang
    Zhao, Yingwen
    JOURNAL OF SURVEYING ENGINEERING, 2019, 145 (01)
  • [44] Toward a unified approach to the total least-squares adjustment
    Hu, Yu
    Fang, Xing
    Zeng, Wenxian
    JOURNAL OF GEODESY, 2024, 98 (08)
  • [45] Theory and algorithm for planar datum establishment using constrained total least-squares
    Shakarji, Craig M.
    Srinivasan, Vijay
    14TH CIRP CAT 2016 - CIRP CONFERENCE ON COMPUTER AIDED TOLERANCING, 2016, 43 : 232 - 237
  • [46] Total Least-Squares Estimation for 2D Affine Coordinate Transformation with Constraints on Physical Parameters
    Zhang, Songlin
    Zhang, Kun
    Liu, Pengcheng
    JOURNAL OF SURVEYING ENGINEERING, 2016, 142 (03)
  • [47] TOTAL LEAST SQUARES IN MODELING: MATLAB TOOLBOX
    Bednarova, Dagmar
    Petras, Ivo
    Podlubny, Igor
    Skovranek, Tomas
    O'Leary, Paul
    PROCEEDINGS OF 11TH INTERNATIONAL CARPATHIAN CONTROL CONFERENCE, 2010, 2010, : 327 - 330
  • [48] A note on the scaled total least squares problem
    Xu, Wei
    Qiao, Sanzheng
    Wei, Yimin
    LINEAR ALGEBRA AND ITS APPLICATIONS, 2008, 428 (2-3) : 469 - 478
  • [49] Overview of total least-squares methods
    Markovsky, Ivan
    Van Huffel, Sabine
    SIGNAL PROCESSING, 2007, 87 (10) : 2283 - 2302
  • [50] On total least squares for quadratic form estimation
    Fang, Xing
    Wang, Jin
    Li, Bofeng
    Zeng, Wenxian
    Yao, Yibin
    STUDIA GEOPHYSICA ET GEODAETICA, 2015, 59 (03) : 366 - 379