Estimation of Significant Wave Height From X-Band Marine Radar Images Based on Ensemble Empirical Mode Decomposition

IF 4 3区地球科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Geoscience and Remote Sensing Letters Pub Date : 2017-08-11 DOI:10.1109/LGRS.2017.2733538

Xinlong Liu, Weimin Huang, E. Gill

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引用次数: 26

Abstract

In this letter, an ensemble empirical mode decomposition (EEMD)-based method is proposed to estimate significant wave height (SWH) from the X-band marine radar sea surface images. First, the data sequence in each radial direction of a radar subimage is decomposed by the EEMD into several intrinsic mode functions (IMFs). A normalization scheme is then applied to the IMFs to obtain their amplitude modulation components. Finally, by adopting a linear model, the SWH is estimated from the sum of the amplitudes from the second to the fifth modes. The method is tested using radar and buoy data collected in a sea trial off the east coast of Canada. The root-mean-square differences with respect to the buoy reference for the SWH estimations using the traditional signal-to-noise-based method, a recent shadowing-based method, and the proposed technique are 0.78, 0.48, and 0.36 m, respectively. The result indicates that the proposed technique produces improvement in the SWH measurements.

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基于集合经验模态分解的x波段海洋雷达图像有效波高估计

在这封信中，提出了一种基于集合经验模式分解（EEMD）的方法来估计X波段海洋雷达海面图像的有效波高（SWH）。首先，EEMD将雷达子图像的每个径向方向上的数据序列分解为几个固有模式函数（IMF）。然后将归一化方案应用于IMF以获得它们的幅度调制分量。最后，通过采用线性模型，根据第二到第五模式的振幅之和来估计SWH。该方法使用在加拿大东海岸进行的海上试验中收集的雷达和浮标数据进行了测试。对于使用传统的基于信噪比的方法、最近的基于阴影的方法和所提出的技术的SWH估计，相对于浮标参考的均方根差分别为0.78、0.48和0.36m。结果表明，所提出的技术在SWH测量中产生了改进。

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来源期刊

IEEE Geoscience and Remote Sensing Letters 工程技术-地球化学与地球物理

CiteScore

7.60

自引率

12.50%

发文量

1113

审稿时长

3.4 months

期刊介绍： IEEE Geoscience and Remote Sensing Letters (GRSL) is a monthly publication for short papers (maximum length 5 pages) addressing new ideas and formative concepts in remote sensing as well as important new and timely results and concepts. Papers should relate to the theory, concepts and techniques of science and engineering as applied to sensing the earth, oceans, atmosphere, and space, and the processing, interpretation, and dissemination of this information. The technical content of papers must be both new and significant. Experimental data must be complete and include sufficient description of experimental apparatus, methods, and relevant experimental conditions. GRSL encourages the incorporation of "extended objects" or "multimedia" such as animations to enhance the shorter papers.