A robust total Kalman filter algorithm with numerical evaluation-Reference-Cited by-同舟云学术

A robust total Kalman filter algorithm with numerical evaluation

Published:2019-01-08 Issue:373 Volume:52 Page:309-316
ISSN:0039-6265
Container-title:Survey Review
language:en
Short-container-title:Survey Review

Author:

Li Sida¹²^ORCID,Liu Lintao¹,Liu Zhiping³,Wang Guocheng¹

Affiliation:

1. State Key Laboratory of Geodesy and Earth’s Dynamics, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, 430077, People’s Republic of China

2. College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, People’s Republic of China

3. School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, People’s Republic of China

Funder

Ministry of Science and Technology of the People’s Republic of China

Publisher

Informa UK Limited

Subject

Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00396265.2018.1563392

Reference41 articles.

1. Weighted total least squares formulated by standard least squares theory

2. Weighted total least squares applied to mixed observation model

3. Weighted total least squares: necessary and sufficient conditions, fixed and random parameters

4. On non-combinatorial weighted total least squares with inequality constraints

5. Weighted total least-squares with constraints: a universal formula for geodetic symmetrical transformations

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