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Modelling of instrument repositioning errors in discontinuous Multi-Campaign Ground-Based SAR (MC-GBSAR) deformation monitoring

Lookup NU author(s): Zheng Wang, Professor Zhenhong Li, Professor Jon Mills

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

© 2019 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Ground-Based SAR (GBSAR) data acquisition in discontinuous mode can be useful for monitoring events whereby deformations become significant over relatively long periods. However, repositioning errors often occur in repeated campaigns and cause inaccuracies in discontinuous GBSAR deformation monitoring. This study firstly investigates the characteristics and quantifies the effects of repositioning errors. Three effects are identified: image shifts, geometric phase ramps, and topographic phase errors. The remainder of this paper then focuses on the modelling and removal of these effects. Images are automatically co-registered through amplitude-based feature matching with a sub-pixel co-registration precision. Whereas traditionally the geometric and topographic phase errors are simply considered as low-frequency signals and removed by filtering, this study presents accurate models for removing these errors. The geometric phase ramps are removed by recovering a 2nd-order polynomial function of the range and azimuth image coordinates. A linear model is introduced to correct the topographic effect without knowing the spatial baseline between different campaigns. Finally, a new combined approach is proposed by merging the geometric and topographic correction models together with a rigorous atmospheric correction model. A new interferometric processing chain is thereby developed on the basis of the proposed combined model for discontinuous Multi-Campaign GBSAR (MC-GBSAR) deformation monitoring. The feasibility of this chain is demonstrated through its application to both synthetic and real-world GBSAR data comprising both moderate and considerable repositioning errors.


Publication metadata

Author(s): Wang Z, Li Z, Mills J

Publication type: Article

Publication status: Published

Journal: ISPRS Journal of Photogrammetry and Remote Sensing

Year: 2019

Volume: 157

Pages: 26-40

Print publication date: 01/11/2019

Online publication date: 04/09/2019

Acceptance date: 30/08/2019

Date deposited: 31/10/2019

ISSN (print): 0924-2716

ISSN (electronic): 1872-8235

Publisher: Elsevier BV

URL: https://doi.org/10.1016/j.isprsjprs.2019.08.019

DOI: 10.1016/j.isprsjprs.2019.08.019


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