An Improved Bayesian von Karman Regularization Method for the Joint Inversion of GNSS and InSAR Data-Reference-Cited by-同舟云学术

An Improved Bayesian von Karman Regularization Method for the Joint Inversion of GNSS and InSAR Data

Published:2023-02 Issue:1 Volume:149 Page:
ISSN:0733-9453
Container-title:Journal of Surveying Engineering
language:en
Short-container-title:J. Surv. Eng.

Author:

Wang Leyang¹^ORCID,Sun Longxiang²,Xu Guangyu³

Affiliation:

1. Professor, Faculty of Geomatics, East China Univ. of Technology, Nanchang 330013, PR China; Professor, Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake, Ministry of Natural Resources, Nanchang 330013, PR China. ORCID: .

2. Master’s Candidate, Faculty of Geomatics, East China Univ. of Technology, Nanchang 330013, PR China (corresponding author).

3. Lecturer, Faculty of Geomatics, East China Univ. of Technology, Nanchang 330013, PR China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29SU.1943-5428.0000409

Reference52 articles.

1. Going to Any Lengths: Solving for Fault Size and Fractal Slip for the 2016, M w 6.2 Central Tottori Earthquake, Japan, Using a Transdimensional Inversion Scheme

2. A Bayesian Method for Incorporating Self-Similarity Into Earthquake Slip Inversions

3. Non-negative least-squares variance component estimation with application to GPS time series

4. Inversion of Surface Deformation Data for Rapid Estimates of Source Parameters and Uncertainties: A Bayesian Approach

5. Physical applications of GPS geodesy: a review

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