星载GNSS-R海浪有效波高反演模型构建

doi:10.11947/j.AGCS.2022.20210284

测绘学报 ›› 2022, Vol. 51 ›› Issue (9): 1920-1930.doi: 10.11947/j.AGCS.2022.20210284

星载GNSS-R海浪有效波高反演模型构建

布金伟^1,2, 余科根^1,2, 韩帅^1,2

1. 中国矿业大学自然资源部国土环境与灾害监测重点实验室, 江苏徐州 221116;
2. 中国矿业大学环境与测绘学院, 江苏徐州 221116

收稿日期:2021-05-19 修回日期:2022-07-27 发布日期:2022-09-29
通讯作者: 余科根 E-mail:kegen.yu@cumt.edu.cn
作者简介:布金伟(1992—),男,博士生,研究方向为GNSS精密定位和GNSS反射遥感。E-mail:b_jinwei@cumt.edu.cn
基金资助:
国家自然科学基金（42174022；41574031）；中国矿业大学未来科学家计划（2020WLKXJ049）；江苏省研究生科研与实践创新计划（KYCX20_2003）

Construction of spaceborne GNSS-R ocean waves significant wave height retrieval model

BU Jinwei^1,2, YU Kegen^1,2, HAN Shuai^1,2

1. MNR Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China;
2. School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China

Received:2021-05-19 Revised:2022-07-27 Published:2022-09-29
Supported by:
The National Natural Science Foundation of China (Nos. 42174022;41574031); The Future Scientists Program of China University of Mining and Technology (No. 2020WLKXJ049); Postgraduate Research & Practice Innovation Program of Jiangsu Province (No. KYCX20_2003)

摘要/Abstract

摘要： 海浪有效波高是描述海况的重要参数，在海浪和海洋动力学的预测中起着重要的作用。然而，卫星雷达高度计和浮标等传统方法难以实现高时空分辨率的SWH估计。星载GNSS-R为估计SWH提供了一种思路。本文提出了一种基于归一化积分延迟波形反演星载GNSS-R海浪SWH的方法。首先，对星载GNSS-R延迟多普勒图进行去噪处理和数据过滤以便对DDM数据进行严格质量控制。然后，从DDM中提取NIDW，并基于NIDW计算4个GNSS-R观测值（即归一化积分时延波形的前沿斜率和前沿波形值之和，归一化积分时延波形的后沿斜率和后沿波形值之和）。随后，基于这4个观测值建立了星载GNSS-R海浪SWH反演经验模型。最后，分别将ERA5和AVISO SWH数据产品作为验证数据，并将反演模型的SWH估计结果与ERA5和AVISO SWH数据产品进行比较和分析。试验结果表明，当采用ERA5 SWH数据作为验证数据时，4个观测值反演SWH的均方根误差和相关系数分别优于0.66 m和0.65；当采用AVISO SWH数据作为验证数据时，4个观测值反演SWH的均方根误差和相关系数分别优于0.68 m和0.70。进一步表明了本文建模方法在星载GNSS-R SWH估计方面具有可行性和可靠性。

关键词: GNSS-R, 延迟多普勒图, 归一化积分时延波形, 有效波高, 经验模型

Abstract: Significant wave height (SWH) is an important parameter to describe the sea state and plays an important role in the prediction of wave and ocean dynamics. However, traditional methods such as satellite radar altimeter and buoy are difficult to achieve high spatial-temporal resolution SWH estimation. As a novel remote sensing technology, spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) provides a new opportunity to estimate SWH. This paper presents a new method for retrieving SWH of spaceborne GNSS-R waves based on normalized integral delay waveform (NIDW). Firstly, the spaceborne GNSS-R delay Doppler maps (DDMs) are denoised and filtered in order to strictly control the quality of DDM data. Then, NIDW is extracted from DDM, and four GNSS-R observables are calculated based on NIDW (i.e. leading edge slope of NIDW, trailing edge slope of NIDW, leading edge waveform summation of NIDW and trailing edge waveform summation of NIDW). Subsequently, based on these four observables, an empirical SWH retrieval model of spaceborne GNSS-R is established. Finally, ERA5 and AVISO SWH data products are used as validation data respectively, and the SWH estimation results of the retrieval model are compared and analyzed with ERA5 and AVISO SWH data products. The experimental results show that when the EAR5 SWH data is used as the verification data, the root mean square error (RMSE) and correlation coefficient (CC) of the four observables are better than 0.66 m and 0.65, respectively. When the AVISO SWH data is used as the verification data, the RMSE and CC of the four observables are better than 0.68 m and 0.70, respectively. It further shows that the modeling method proposed in this paper is feasible and reliable in spaceborne GNSS-R SWH estimation.

Key words: GNSS-R, delay-Doppler maps, normalized integral delay waveform, significant wave height, empirical model

中图分类号:

P237

布金伟, 余科根, 韩帅. 星载GNSS-R海浪有效波高反演模型构建[J]. 测绘学报, 2022, 51(9): 1920-1930.

BU Jinwei, YU Kegen, HAN Shuai. Construction of spaceborne GNSS-R ocean waves significant wave height retrieval model[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(9): 1920-1930.

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星载GNSS-R海浪有效波高反演模型构建

Construction of spaceborne GNSS-R ocean waves significant wave height retrieval model

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