Comparison of Structured and Weighted Total Least-Squares Adjustment Methods for Linearly Structured Errors-in-Variables Models
作者:Zhou, YJ (Zhou, Yongjun)[ 1 ] ; Kou, XJ (Kou, Xinjian)[ 1 ] ; Li, J (Li, Jonathan)[ 2 ] ; Fang, X (Fang, Xing)[ 3 ]
JOURNAL OF SURVEYING ENGINEERING
卷: 143
期: 1
文献号: UNSP 04016019DOI: 10.1061/(ASCE)SU.1943-5428.0000190
出版年: FEB 2017
摘要
The paper focuses on a specific errors-in-variables (EIV) model named the linearly structured EIV (LSEIV) model in which all the random elements of design matrix are in a linear combination of an input vector with random errors. Two existing structured total least-squares (STLS) algorithms named constrained TLS (CTLS) and structured TLS normalization (STLN) are introduced to solve the LSEIV model by treating the input and output vectors as the noisy structure vectors. For comparison purposes, the weighted TLS (WTLS) method is also performed based on the partial EIV model. Approximated accuracy assessment methods are also presented. The plane fitting and Bursa transformation examples are illustrated to demonstrate the accuracy and computational efficiency performance of the proposed algorithms. It shows that the proposed STLS and WTLS algorithms can achieve the same accuracy if the dispersion matrix of the WTLS method is constructed based on the partial EIV model.
关键词
作者关键词:Errors-in-variables (EIV) model; Structured total least-squares (STLS); Weighted total least-squares (WTLS); Linearly structured
KeyWords Plus:DATUM TRANSFORMATION; MATRICES; CONSTRAINTS; REGRESSION; ESTIMATOR; NORM
作者信息
通讯作者地址: Zhou, YJ (通讯作者)
Shanghai Jiao Tong Univ, Schoo1 Naval Architecture Ocean & Civil Engn, Shanghai 200240, Peoples R China. |
地址:
[ 2 ] Univ Waterloo, Fac Environm, Waterloo, ON N2L 3G1, Canada | |
[ 3 ] Wuhan Univ, Sch Geodesy & Geomat, Wuhan 430079, Peoples R China |
电子邮件地址:[email protected]
出版商
ASCE-AMER SOC CIVIL ENGINEERS, 1801 ALEXANDER BELL DR, RESTON, VA 20191-4400 USA
类别 / 分类
研究方向:Engineering
Web of Science 类别:Engineering, Civil
文献信息
文献类型:Article
语种:English
入藏号: WOS:000393862000001
ISSN: 0733-9453
eISSN: 1943-5428
期刊信息
Impact Factor (影响因子):0.884