Artificial Intelligence In Interferometric Synthetic Aperture Radar Phase Unwrapping: A Review

被引:54
|
作者
Zhou, Lifan [1 ,2 ]
Yu, Hanwen [3 ,4 ]
Lan, Yang [5 ]
Xing, Mengdao [6 ,7 ]
机构
[1] Changshu Inst Technol, Sch Comp Sci & Engn, Suzhou 215500, Peoples R China
[2] Chinese Univ Hong Kong, Hong Kong, Peoples R China
[3] Univ Houston, Dept Civil & Environm Engn, Natl Ctr Airborne Laser Mapping, Houston, TX 77004 USA
[4] Univ Elect Sci & Technol China, Sch Resources & Environm, Chengdu 611731, Peoples R China
[5] Xidian Univ, Acad Adv Interdisciplinary Res, Xian 710071, Peoples R China
[6] Xidian Univ, Natl Lab Radar Signal Proc, Xian 710071, Peoples R China
[7] Xidian Univ, Acad Adv Interdisciplinary Res Dept, Xian, Peoples R China
基金
中国国家自然科学基金;
关键词
Artificial intelligence; Synthetic aperture radar; Estimation; Strain; Volcanoes; Surface topography; Remote sensing; CONVOLUTIONAL NEURAL-NETWORK; SAR INTERFEROMETRY; RECONSTRUCTION; MULTIFREQUENCY; ELEVATION; INTERFEROGRAMS; ALGORITHM;
D O I
10.1109/MGRS.2021.3065811
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
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.
引用
收藏
页码:10 / 28
页数:19
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