Algorithms and statistical analysis for linear structured weighted total least squares problem

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成果类型：

期刊论文

作者：

Jian Xie*;Tianwei Qiu;Cui Zhou;Dongfang Lin;Sichun Long

通讯作者：

Jian Xie

作者机构：

[Long S.; Xie J.; Qiu T.] School of Earth Science and Spatial Information Engineering, Hunan University of Science and Technology, Xiangtan, 411201, China

[Zhou C.] College of Science, Central South University of Forestry and Technology, Changsha, 410018, China

[Lin D.] National-Local Joint Engineering Laboratory of Geo-spatial Information Technology, Hunan University of Science and Technology, Xiangtan, 411201, China

通讯机构：

[Jian Xie] S

School of Earth Science and Spatial Information Engineering, Hunan University of Science and Technology, Xiangtan 411201, China

语种：

英文

关键词：

Accuracy evaluation;Errors-in-observations;Errors-in-variables;Functional model modification;Linear structured weighted total least squares;Stochastic model modification

期刊：

大地测量与地球动力学(英)

ISSN：

1674-9847

年：

2024

卷：

期：

页码：

177-188

DOI：

10.1016/j.geog.2023.06.001

基金类别：

The authors would like to acknowledge the financial support of the National Natural Science Foundation of China (Grant No. 42074016 , 42104025 , 42274057 and 41704007 ), Hunan Provincial Natural Science Foundation of China (Grant No. 2021JJ30244 ), Scientific Research Fund of Hunan Provincial Education Department (Grant No. 22B0496 ).

机构署名：

本校为其他机构

院系归属：

理学院

摘要：

Weighted total least squares (WTLS) have been regarded as the standard tool for the errors-in-variables (EIV) model in which all the elements in the observation vector and the coefficient matrix are contaminated with random errors. However, in many geodetic applications, some elements are error-free and some random observations appear repeatedly in different positions in the augmented coefficient matrix. It is called the linear structured EIV (LSEIV) model. Two kinds of methods are proposed for the LSEIV model from functional and stochastic mod...

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Algorithms and statistical analysis for linear structured weighted total least squares problem

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