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Artificial Intelligence In Interferometric Synthetic Aperture Radar Phase Unwrapping: A Review
IEEE Geoscience and Remote Sensing Magazine  (IF8.225),  Pub Date : 2021-04-21, DOI: 10.1109/mgrs.2021.3065811
Lifan Zhou, Hanwen Yu, Yang Lan, mengdao xing

Interferometric synthetic aperture radar (InSAR) is a radar technique widely used in geodesy and remote sensing applications, e.g., topography reconstruction and subsidence estimation. Phase unwrapping (PU) is one of the key procedures of InSAR signal processing. Artificial intelligence (AI) techniques have proven to be potentially powerful in many fields and have been introduced into the PU domain, achieving superior performance. In this article, we provide a comprehensive overview of AI-based PU techniques in InSAR. We survey the AI-based single-baseline (SB) PU methods and then review the AI techniques related to multibaseline (MB) PU. In addition, we show several experimental examples of these methods, from both simulated and real InSAR data sets, which gives readers an overview of AI-based PU processing's potential and limitations. It is our hope that this article will provide researchers with guidelines and inspiration to further enhance the development of AI-based PU.