Estimation of Swell Height Using Spaceborne GNSS-R Data from Eight CYGNSS Satellites

被引:16
|
作者
Bu, Jinwei [1 ,2 ,3 ]
Yu, Kegen [1 ,2 ]
Park, Hyuk [3 ]
Huang, Weimin [4 ]
Han, Shuai [1 ,2 ]
Yan, Qingyun [5 ]
Qian, Nijia [1 ,2 ]
Lin, Yiruo [1 ,2 ]
机构
[1] China Univ Min & Technol, MNR Key Lab Land Environm & Disaster Monitoring, Xuzhou 221116, Jiangsu, Peoples R China
[2] China Univ Min & Technol, Sch Environm Sci & Spatial Informat, Xuzhou 221116, Jiangsu, Peoples R China
[3] Univ Politecn Cataluna, Dept Phys, Barcelona 08034, Spain
[4] Mem Univ Newfoundland, Dept Elect & Comp Engn, St John, NL A1B 3X5, Canada
[5] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing 210044, Peoples R China
基金
中国国家自然科学基金;
关键词
Global Navigation Satellite System-Reflectometry (GNSS-R); Cyclone Global Navigation Satellite System (CYGNSS); delay-Doppler maps (DDMs); swell height; particle swarm optimization (PSO); simulated annealing (SA); SIGNIFICANT WAVE HEIGHT; OCEAN; SEA; EXTRACTION; INVERSION;
D O I
10.3390/rs14184634
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Global Navigation Satellite System (GNSS)-Reflectometry (GNSS-R) technology has opened a new window for ocean remote sensing because of its unique advantages, including short revisit period, low observation cost, and high spatial-temporal resolution. In this article, we investigated the potential of estimating swell height from delay-Doppler maps (DDMs) data generated by spaceborne GNSS-R. Three observables extracted from the DDM are introduced for swell height estimation, including delay-Doppler map average (DDMA), the leading edge slope (LES) of the integrated delay waveform (IDW), and trailing edge slope (TES) of the IDW. We propose one modeling scheme for each observable. To improve the swell height estimation performance of a single observable-based method, we present a data fusion approach based on particle swarm optimization (PSO). Furthermore, a simulated annealing aided PSO (SA-PSO) algorithm is proposed to handle the problem of local optimal solution for the PSO algorithm. Extensive testing has been performed and the results show that the swell height estimated by the proposed methods is highly consistent with reference data, i.e., the ERA5 swell height. The correlation coefficient (CC) is 0.86 and the root mean square error (RMSE) is 0.56 m. Particularly, the SA-PSO method achieved the best performance, with RMSE, CC, and mean absolute percentage error (MAPE) being 0.39 m, 0.92, and 18.98%, respectively. Compared with the DDMA, LES, TES, and PSO methods, the RMSE of the SA-PSO method is improved by 23.53%, 26.42%, 30.36%, and 7.14%, respectively.
引用
收藏
页数:22
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