Litcius/Paper detail

Analysis of Significant Wave Height From X-Band Radar Images Based on Empirical Wavelet Transform

Shaoyan Zuo, Dazhi Wang, Liujia Suo, Shuaiwu Liu, Yongqing Zhao, Dewang Liu

2024IEEE Geoscience and Remote Sensing Letters12 citationsDOI

Abstract

This letter proposes an empirical wavelet transform (EWT)-based method to analyze significant wave heights ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> ) from X-band marine radar images. First, each azimuth of the selected radar sub-image is decomposed by the EWT into different numbers of intrinsic mode functions (IMFs). Then, the information entropy is used to filter the amplitude modulation (AM) portions extracted from the IMFs. Finally, a linear fitting method is established by the average of the filtered AM in range and azimuth, respectively. The testing data are collected from shore-based radar and wave buoy in Pingtan, Fujian, China. The experimental results show that the proposed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> analysis method is improved compared with the signal-to-noise (SNR)-based method and the ensemble empirical mode decomposition (EEMD)-based method. The root mean square error (RMSE) is decreased by 0.25 m and 0.10 m, respectively. Further, the correlation coefficient is increased by 0.23 and 0.06, respectively.

Topics & Concepts

Wavelet transformWaveletRadar imagingRemote sensingComputer scienceRadarGeologyArtificial intelligenceTelecommunicationsOcean Waves and Remote SensingSoil Moisture and Remote SensingRadar Systems and Signal Processing