Research on Sea Surface Wind Speed FM Based on CYGNSS and HY-2B Microwave Scatterometer

作者：Yun Zhang, Xingyu Zhao, Shuhu Yang, Yanling Han, Zhonghua Hong, Wanting Meng, Zhansheng Chen, Weiliang Liu · 发表于：IEEE Transactions on Geoscience and Remote Sensing · 年份：2024 · DOI：10.1109/tgrs.2024.3363705 · 被引用次数：9 · 研究领域：Soil Moisture and Remote Sensing、Ocean Waves and Remote Sensing、Underwater Acoustics Research

GNSS-R technology for the retrieval of sea surface wind speed (SW) has gradually matured, and many research results in terms of methodology and accuracy have been obtained. Multisource data fusion has been a major trend in remote sensing research in recent years. However, there are few fusion algorithms in SW retrieval, and most of them retrieve the SW of a single data source. Based on the principle of CYGNSS forward scattering and HY-2B microwave scatterometer (HSCAT-B) backscattering, this paper proposes a Fusion Model (FM) of SW based on CYGNSS and HSCAT-B. For CYGNSS SW inversion using the FM, there is no need to input HSCAT-B data, and the accuracy of CYGNSS SW inversion above 10 m/s is improved. Based on the true SW data of the European Center for Medium-Range Weather Forecasts (ECMWF), the root mean square error (RMSE) of SW inversion is improved from 2.517 m/s and 1.645 m/s with a single data source to 1.527 m/s with the FM. To further correct the outliers of the FM, the result fitting model is added after the FM. The experimental results show that the RMSE of the result fitting model is improved from 1.527 m/s for the FM to 1.489 m/s. Finally, CYGNSS L2 SW and the National Data Buoy Center (NDBC) data is used to verify the inversion results, the RMSE of the result fitting model is 1.688 m/s and 1.60 m/s, respectively. The results prove the feasibility of a fusion algorithm for SW using multisource data.