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Time Series Phase Unwrapping Based on Graph Theory and Compressed Sensing

Ma, Zhang-Feng and Jiang, Mi and Khoshmanesh, Mostafa and Cheng, Xiao (2021) Time Series Phase Unwrapping Based on Graph Theory and Compressed Sensing. IEEE Transactions on Geoscience and Remote Sensing . ISSN 0196-2892. doi:10.1109/TGRS.2021.3066784. (In Press)

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Time Series SAR interferometry (InSAR) (TS-InSAR) has been widely applied to monitor the crustal deformation with centimeter- to millimeter-level accuracy. Phase unwrapping (PU) errors have proven to be one of the main sources of bias that hinder achieving such high accuracy. In this article, a new time series PU approach is developed to improve the unwrapping accuracy. The rationale behind the proposed method is to first improve the sparse unwrapping by mitigating the phase gradients in a 2-D network and then correcting the unwrapping errors in time, based on the triplet phase closure. Rather than the commonly used Delaunay network, we employ the all-pairs-shortest-path (APSP) algorithm from graph theory to maximize the temporal coherence of all edges and to approach the phase continuity assumption in the 2-D spatial domain. Next, we formulate the PU error correction in the 1-D temporal domain as compressed sensing (CS) problem, according to the sparsity of the remaining phase ambiguity cycles. We finally estimate phase ambiguity cycles by means of integer linear programming (ILP). The comprehensive comparisons using synthetic and real Sentinel-1 data covering Lost Hills, California, confirm the validity of the proposed 2-D + 1-D unwrapping approach and its superior performance compared to previous methods.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Ma, Zhang-Feng0000-0003-0044-7710
Jiang, Mi0000-0003-2459-4619
Khoshmanesh, Mostafa0000-0001-8724-5737
Additional Information:© 2021 IEEE. Manuscript received December 7, 2020; revised January 27, 2021 and March 1, 2021; accepted March 13, 2021. This work was supported in part by the National Natural Science Foundation of China under Grant 41774003 and Grant 42074008, in part by the European Space Agency (ESA), Ministry of Science and Technology (MOST) of China Dragon 5 Project under Grant 59332, and in part by the Program of China Scholarship Council under Grant 202006710013.
Funding AgencyGrant Number
National Natural Science Foundation of China41774003
National Natural Science Foundation of China42074008
European Space Agency (ESA)UNSPECIFIED
Ministry of Science and Technology (Taipei)59332
China Scholarship Council202006710013
Subject Keywords:All-pairs-shortest-path (APSP), compressed sensing (CS), graph theory, phase unwrapping (PU), SAR interferometry (InSAR), time series
Record Number:CaltechAUTHORS:20210412-102922432
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Official Citation:Z. -F. Ma, M. Jiang, M. Khoshmanesh and X. Cheng, "Time Series Phase Unwrapping Based on Graph Theory and Compressed Sensing," in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2021.3066784
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:108697
Deposited By: Tony Diaz
Deposited On:13 Apr 2021 23:24
Last Modified:19 Apr 2021 18:07

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