Wind Speed Extraction Based on High Frequency Radar Retrieved Wind-Driven Current

被引:4
|
作者
Wen, Cui [1 ]
Tian, Yingwei [1 ]
Wen, Biyang [1 ]
机构
[1] Wuhan Univ, Sch Elect Informat, Wuhan 430072, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Wind speed; Sea surface; High frequency radar; Current measurement; Sea measurements; Radar measurements; Artificial neural network; high frequency (HF) radar; wind speed extraction; wind-driven current; SURFACE CURRENTS; PERFORMANCE;
D O I
10.1109/LGRS.2020.3004402
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
High frequency (HF) radar often indirectly inverts wind field from wave height field, so the accuracy, range, and spatial resolution of the estimated wind field are usually limited by the wave field estimation performance. However, the sea surface current including the wind-driven current can often be accurately measured by radar. Thus, based on the wind-driven current estimated by HF radar, a new wind speed inversion algorithm is proposed in this letter. First, the relationship between wind speed and wind-driven current speed is established according to the ocean dynamics theory, but it contains several uncertain parameters. To avoid solving these parameters, an artificial neural network is used to train an accurate model between wind-driven current speed and wind speed. Final, the wind-driven current estimated by radar is substituted into the model to extract wind speed. A field experiment shows that the average correlation coefficient between the radar-estimated wind speed and the reference wind speed is 0.86, and the average root mean square error is 2.38 m/s. In addition, the proposed algorithm has larger measurement range and better spatial resolution than traditional algorithms.
引用
收藏
页码:1555 / 1559
页数:5
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