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Lookup NU author(s): Zheng Wang, Professor Zhenhong Li, Professor Jon MillsORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© 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.
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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