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基于人工神经网络的高频雷达风速反演

蔡佳佳 曾玉明 周浩 文必洋

蔡佳佳,曾玉明,周浩,等. 基于人工神经网络的高频雷达风速反演[J]. 海洋学报,2019,41(11):150–155,doi:10.3969/j.issn.0253−4193.2019.11.014
引用本文: 蔡佳佳,曾玉明,周浩,等. 基于人工神经网络的高频雷达风速反演[J]. 海洋学报,2019,41(11):150–155,doi:10.3969/j.issn.0253−4193.2019. 11.014
Cai Jiajia,Zeng Yuming,Zhou Hao, et al. Wind speed inversion of high frequency radar based on artifical neural network[J]. Haiyang Xuebao,2019, 41(11):150–155,doi:10.3969/j.issn.0253−4193.2019.11.014
Citation: Cai Jiajia,Zeng Yuming,Zhou Hao, et al. Wind speed inversion of high frequency radar based on artifical neural network[J]. Haiyang Xuebao,2019, 41(11):150–155,doi:10.3969/j.issn.0253−4193.2019.11.014

基于人工神经网络的高频雷达风速反演

doi: 10.3969/j.issn.0253-4193.2019.11.014
基金项目: 国家自然科学基金(61371198);国家重大科学仪器设备开发专项(2013YQ160793)。
详细信息
    作者简介:

    蔡佳佳(1995—),女,浙江省湖州市人,主要从事雷达信号处理研究。E-mail:caijiajia@whu.edu.cn

    通讯作者:

    周浩(1978—),男,教授,主要从事高频雷达海洋环境监测技术研究。E-mail:zhou.h@whu.edu.cn

  • 中图分类号: TN958;P715

Wind speed inversion of high frequency radar based on artifical neural network

  • 摘要: 风速是重要的海洋状态参数之一,对海面风速的准确提取是实现海洋环境监测和沿海工程应用的重要保证。目前,作为新兴海洋环境监测设备,高频雷达在风速提取方面仍然存在挑战。本文提出了一种基于人工神经网络的风速提取方法,利用历史浮标测量海态数据训练风速提取网络,实现风速与有效波高、波周期、风向及时间因素之间的非线性映射。测试结果表明了这一网络在时间和空间上的稳定性;进而将已训练的网络应用到便携式高频地波雷达OSMAR-S的风速反演中,得到的风速与浮标测量风速间的相关系数达到0.849,均方根误差为2.11 m/s。这一结果明显优于常规由浪高反演风速的SMB方法,验证了该方法在高频雷达风速反演中的可行性。
  • 图  1  风速反演神经网络基本结构

    Fig.  1  Basic structure of wind speed inversion neural network

    图  2  网络训练及测试所用浮标位置

    Fig.  2  Buoy position used for network training and testing

    图  3  人工神经网络风速反演结果

    a. ANN反演风速与浮标测量风速序列的对比;b. ANN反演风速与浮标测量风速散点图

    Fig.  3  Wind speed inversion results of artificial neural network

    a. Comparison of wind speed inverted by ANN and wind speed measured by buoys; b. scatter plots of wind speed inverted by ANN and wind speed measured by buoys

    图  4  SMB风速反演结果

    a. SMB反演风速与浮标测量风速序列的对比;b. SMB反演风速与浮标测量风速散点图

    Fig.  4  Wind speed inversion results of SMB

    a. Comparison of wind speed inverted by SMB and wind speed measured by buoys; b. scatter plots of wind speed inverted by SMB and wind speed measured by buoys

    图  5  两种网络的风速反演均方根误差和相关系数对比

    Fig.  5  Comparison of wind speed root mean square error and correlation coefficient inverted by two networks

    图  6  福建实验地理位置

    Fig.  6  Geographic location of experiments in the Fujian adjacent waters

    图  7  C浮标处ANN风速反演结果

    a. ANN反演风速与浮标测量风速序列的对比;b. ANN反演风速与浮标测量风速散点图

    Fig.  7  Wind speed inversion result of ANN at C buoy

    a. Comparison of wind speed inverted by ANN and wind speed measured by buoys; b. scatter plots of wind speed inverted by ANN and wind speed measured by buoys

    图  8  雷达实验风速反演结果

    a. 雷达实验反演风速与浮标风速序列对比;b. ANN反演风速与浮标风速序列散点图

    Fig.  8  Wind speed inversion results of radar experiment

    a. Comparison of wind speed inverted by radar experiment and wind speed measured by buoys; b. scatter plots of wind speed inverted by ANN and wind speed measured by buoys

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  • 被引次数: 0
出版历程
  • 收稿日期:  2018-09-16
  • 修回日期:  2018-11-15
  • 网络出版日期:  2021-04-21
  • 刊出日期:  2019-11-25

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