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星载SAR海面风场与海浪遥感探测研究综述
A Review of Spaceborne SAR Sea Surface Wind Field and Wave Remote Sensing Detection
  
DOI:doi:10.3969/j.issn.1003-2029.2025.04.002
中文关键词:  合成孔径雷达  海面风场  海浪  遥感探测  反演方法
英文关键词:Synthetic Aperture Radar  sea surface wind field  ocean waves  remote sensing detection  inversion method
基金项目:国家自然科学基金资助项目(61931025)
作者单位
祝源,万勇,孙伟峰 (中国石油大学(华东) 海洋与空间信息学院,山东 青岛 266580) 
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中文摘要:
      海面风场和海浪是两种关键的海洋动力过程,是与人类活动最直接相关的海洋现象。海浪 和风场是研究海洋环境的重要因素,传统的海浪和风场测量方法测量范围小且易受到天气条件的限 制,而星载合成孔径雷达(Synthetic Aperture Radar,SAR) 具有较高的空间分辨率,能够提供大 范围、高精度的海浪和风场信息,在海面风场和海浪监测中逐渐展现出其独特的优势。本文系统地 概述了SAR 海面风场和海浪反演的研究现状,阐述了SAR 在海面风场和海浪遥感探测中的机理, 总结了近十年来常用的SAR 海浪和风场反演方法,分析了国内外在该领域的研究进展及存在的不 足之处。本文还针对高海况下SAR 海面风场参数反演和SAR 海浪参数反演进行了深入分析,探讨 了各种算法的适用性与局限性。此外,本文还展望了未来的研究方向,指出在提高海浪和风场参数 反演精度和适应复杂海况方面的挑战。随着科技发展,结合多源遥感数据与机器学习方法,为SAR 海面风场与海浪反演提供新的解决方案。同时,数据处理效率的提升和实时监测能力的提高,也将 进一步推动SAR 技术在海洋监测中的应用,为全面认知海洋环境变化与气候系统的耦合机制提供 科学支撑。
英文摘要:
      Sea surface wind field and ocean waves are two key oceanic dynamic processes, which are the most directly related to human activities. Wave wind field is an important factor in the study of marine environment, and the traditional wave wind field measurement method has a small measurement range and is easily limited by weather conditions, while spaceborne Synthetic Aperture Radar (SAR) has high spatial resolution and can provide large-range, high-precision wave wind field information, and gradually shows its unique advantages in sea surface wind field and wave monitoring.In this paper, we first systematically summarize the research status of SAR sea surface wind field and wave inversion, and expound the mechanism of SAR in sea surface wind field and wave remote sensing detection. Subsequently, this paper summarizes the commonly used SAR wave wind field inversion methods in the past decade, and analyzes the research progress and shortcomings in this field at home and abroad. In particular, this paper conducts an in-depth analysis of the inversion of SAR sea surface wind field parameters and SAR wave parameters under high sea conditions, and discusses the applicability and limitations of various algorithms. In addition, this paper also looks forward to future research directions, and points out the challenges in improving the accuracy of wave wind field parameter inversion and adapting to complex sea conditions. With the development of science and technology, the combination of multi-source remote sensing data and advanced machine learning methods provides new solutions for SAR sea surface wind field and wave inversion. At the same time, the improvement of data processing efficiency and the enhancement of real-time monitoring capabilities will further promote the application of SAR technology in marine monitoring, and help to understand marine environmental changes and their impact on climate more comprehensively.
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