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Remote Sensing
Volume 15
Issue 19
10.3390/rs15194885
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Article

A Robust InSAR Phase Unwrapping Method via Improving the pix2pix Network

by
Long Zhang
1,2,
Guoman Huang
2,
Yutong Li
2,3,
Shucheng Yang
2,*,
Lijun Lu
2 and
Wenhao Huo
2,3
1
School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
2
Chinese Academy of Surveying and Mapping, Beijing 100036, China
3
College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(19), 4885; https://doi.org/10.3390/rs15194885
Submission received: 16 September 2023 / Revised: 30 September 2023 / Accepted: 2 October 2023 / Published: 9 October 2023
(This article belongs to the Section AI Remote Sensing)
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Abstract

The main core of InSAR (interferometric synthetic aperture radar) data processing is phase unwrapping, and the output has a direct impact on the quality of the data processing products. Noise introduced from the SAR system and interferometric processing is unavoidable, causing local phase inaccuracy and limiting the unwrapping results of traditional unwrapping methods. With the successful implementation of deep learning in a variety of industries in recent years, new concepts for phase unwrapping have emerged. This research offers a one-step InSAR phase unwrapping method based on an improved pix2pix network model. We achieved our aim by upgrading the pix2pix network generator model and introducing the concept of quality map guidance. Experiments on InSAR phase unwrapping utilizing simulated and real data with different noise intensities were carried out to compare the method with other unwrapping methods. The experimental results demonstrated that the proposed method is superior to other unwrapping methods and has a good robustness to noise.
Keywords: interferometric synthetic aperture radar; phase unwrapping; deep learning; pix2pix interferometric synthetic aperture radar; phase unwrapping; deep learning; pix2pix

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MDPI and ACS Style

Zhang, L.; Huang, G.; Li, Y.; Yang, S.; Lu, L.; Huo, W. A Robust InSAR Phase Unwrapping Method via Improving the pix2pix Network. Remote Sens. 2023, 15, 4885. https://doi.org/10.3390/rs15194885

AMA Style

Zhang L, Huang G, Li Y, Yang S, Lu L, Huo W. A Robust InSAR Phase Unwrapping Method via Improving the pix2pix Network. Remote Sensing. 2023; 15(19):4885. https://doi.org/10.3390/rs15194885

Chicago/Turabian Style

Zhang, Long, Guoman Huang, Yutong Li, Shucheng Yang, Lijun Lu, and Wenhao Huo. 2023. "A Robust InSAR Phase Unwrapping Method via Improving the pix2pix Network" Remote Sensing 15, no. 19: 4885. https://doi.org/10.3390/rs15194885

APA Style

Zhang, L., Huang, G., Li, Y., Yang, S., Lu, L., & Huo, W. (2023). A Robust InSAR Phase Unwrapping Method via Improving the pix2pix Network. Remote Sensing, 15(19), 4885. https://doi.org/10.3390/rs15194885

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