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.

中文翻译：

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干涉合成孔径雷达相位展开中的人工智能：综述

干涉合成孔径雷达 (InSAR) 是一种广泛用于大地测量和遥感应用的雷达技术，例如地形重建和沉降估计。相位解缠(PU)是InSAR信号处理的关键过程之一。人工智能 (AI) 技术已被证明在许多领域具有潜在的强大功能，并已被引入 PU 领域，实现了卓越的性能。在本文中，我们全面概述了 InSAR 中基于 AI 的 PU 技术。我们调查了基于 AI 的单基线 (SB) PU 方法，然后回顾了与多基线 (MB) PU 相关的 AI 技术。此外，我们展示了这些方法的几个实验示例，来自模拟和真实 InSAR 数据集，让读者了解基于 AI 的 PU 处理的潜力和局限性。