基于高分三号SAR图像的海面起伏场准线性反演

房玉鑫; 范陈清; 孟俊敏; 张杰; 闫秋双

doi:10.12000/JR25146

基于高分三号SAR图像的海面起伏场准线性反演

DOI: 10.12000/JR25146 CSTR: 32380.14.JR25146

房玉鑫¹,
范陈清²,
孟俊敏²,
张杰^{1, 2},
闫秋双^1, ,

1.
中国石油大学(华东) 青岛 266580
2.
自然资源部第一海洋研究所青岛 266061

基金项目: 国家自然科学基金(42206178)

详细信息

作者简介:
房玉鑫，博士生，主要研究方向为深度学习与SAR海洋遥感应用

范陈清，副研究员，主要研究方向为海洋微波遥感

孟俊敏，研究员，主要研究方向为SAR海洋遥感应用、海洋内波遥感探测技术研究

张　杰，研究员，主要研究方向为海洋遥感遥测研究

闫秋双，副教授，主要研究方向为海洋微波遥感

通讯作者:
闫秋双yanqiushuang@upc.edu.cn

责任主编：王小青 Corresponding Editor: WANG Xiaoqing

中图分类号: TN95
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出版历程
- 收稿日期: 2025-08-01
- 修回日期: 2026-02-01

A Quasi-linear Inversion Algorithm for Retrieving Sea Surface Elevation from GF-3 SAR Images

1.
China University of Petroleum (East China), Qingdao 266580, China
2.
First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China

Funds: The National Natural Science Foundation of China under Grant (42206178)

More Information

Corresponding author: YAN Qiushuang, yanqiushuang@upc.edu.cn

摘要

摘要: 通过对海面起伏场进行分析，不仅可获取常用的海浪统计参数，还能细致描述单个波浪的特性、检测异常巨浪、研究波群与波组的演变过程，从而更精准地描述大面积非均匀海况。该文基于准线性模型，提出一套适用于高分三号合成孔径雷达(SAR)图像的海面起伏场反演方案。该方案不依赖外部辅助数据，可在10 s内完成单景SAR数据的海面起伏场快速反演，并有效提取沿距离向传播的波浪信息。通过3种典型海况下的反演实例，体现出该方法在提取最大波高、识别波群与波组结构等方面的优势。进一步将2405景高分三号波模式SAR图像的反演结果与ERA5再分析海浪谱及高度计实测数据进行对比。结果显示，反演有效波高与ERA5数据的均方根误差为0.48 m。在有效波高低于3 m的中低海况下，反演有效波高与ERA5及高度计数据均保持良好一致性。本研究为基于高分3号SAR的海况信息快速监测与分析提供了有效工具。
- 合成孔径雷达 /
- 高分三号 /
- 海面起伏场 /
- 准线性模型 /
- 快速反演
Abstract: Sea surface elevation is crucial for characterizing individual waves, wave groups, and freak waves, offering an accurate representation of inhomogeneous sea states. This study presents a quasi-linear inversion strategy for retrieving sea surface elevation from GF-3 Synthetic Aperture Radar (SAR) images. The algorithm enables rapid inversion within 10 s per scene without the need for external data and effectively resolves range-traveling waves. Case studies conducted under three distinct sea states demonstrate its ability to extract maximum wave heights and identify wave groups. Additionally, inversion results from 2405 GF-3 wave mode SAR images following quality control are compared with ERA5 reanalysis spectra and altimeter data. The comparisons reveal that the retrieved Significant Wave Height (SWH) has a root mean square error of 0.48 m compared with ERA5 data. In low-to-moderate sea states, with significant wave heights below 3 m, the retrieved SWH shows strong consistency with ERA5 spectra and altimeter measurements. This algorithm serves as an effective tool for rapid monitoring and analysis of sea states using GF-3 SAR.
- Synthetic Aperture Radar (SAR) /
- GF-3 /
- Sea surface elevation /
- Quasi-linear model /
- Rapid inversion

HTML全文

图 1 SARAL高度计测量与ERA5海浪谱有效波高散点图

Figure 1. The scatter plot between the significant wave height of SARAL measurements and ERA5 wave spectra

下载: 全尺寸图片幻灯片

图 2 基于GF-3 波模式SAR图像的海面起伏场反演流程图

Figure 2. The schematic of the entire framework of two-dimensional sea surface elevation retrieval from GF-3 SAR wave mode data.

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图 3 海面起伏场反演示例1

Figure 3. Case study 1 of the sea surface elevation retrieval.

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图 4 海面起伏场反演示例2

Figure 4. Case study 2 of the sea surface elevation retrieval

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图 5 海面起伏场反演示例3

Figure 5. Case study 3 of the sea surface elevation retrieval

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图 6 起伏场反演结果与ERA5海浪谱数据计算得到的海浪特征参数对比

Figure 6. The comparison between the wave integrating parameters computed from retrieved sea surface elevations and those from ERA5 wave spectra

下载: 全尺寸图片幻灯片

图 7 反演起伏场计算的有效波高与高度计测量值的散点对比。横轴和纵轴分别代表由高度计和由反演起伏场计算得到的有效波高值

Figure 7. The scatter comparison between the significant wave height computed from retrieved sea surface elevations and those from the altimeter measurements

下载: 全尺寸图片幻灯片

表 1 ：不同ERA5有效波高区间下的海浪积分参数对比

Table 1. The comparison of wave integrating parameters under different intervals of ERA5 significant wave heights

海况类别	样本数量	有效波高 $ {H}_{\mathrm{s}} $			平均波周期 $ {T}_{\text{mw}} $
海况类别	样本数量	RMSE (m)	Bias (m)	Corr	RMSE (s)	Corr
$ {H}_{\mathrm{s}} $ < 1.5 m	392	0.156	0.052	0.721	1.158	0.623
1.5 m < $ {H}_{\mathrm{s}} $ < 3 m	1,759	0.463	0.186	0.537	1.174	0.649
$ {H}_{\mathrm{s}} $ > 3 m	254	0.829	0.427	0.526	1.176	0.681

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