Estimation of Significant Wave Heights from X-Band Radar Based on ANN Using CNN Rainfall Classifier

Abstract

Wave observations using a marine X-band radar are conducted by analyzing the backscattered radar signal from sea surfaces. Wave parameters are extracted using Modulation Transfer Function obtained from 3D wave number and frequency spectra which are calculated by 3D FFT of time series of sea surface images (42 images per minute). The accuracy of estimation of the significant wave height is, therefore, critically dependent on the quality of radar images. Wave observations during Typhoon Maysak and Haishen in the summer of 2020 show large errors in the estimation of the significant wave heights. It is because of the deteriorated radar images due to raindrops falling on the sea surface. This paper presents the algorithm developed to increase the accuracy of wave heights estimation from radar images by adopting convolution neural network(CNN) which automatically classify radar images into rain and non-rain cases. Then, an algorithm for deriving the Hs is proposed by creating different ANN models and selectively applying them according to the rain or non-rain cases. The developed algorithm applied to heavy rain cases during typhoons and showed critically improved results.

Wave Height and Period Estimation from X-Band Marine Radar Images Using Convolutional Neural Network

“…It is worth noting that machine learning algorithms have been applied to H s estimation, which can simplify the cumbersome steps of previous algorithms and improve computational efficiency. It is also possible to estimate more accurate results using methods including a support vector regression (SVR)-based method [24], artificial neural network (ANN)-based methods [25,26], a convolutional neural network (CNN)-based method [27], a convolutional gated recurrent unit network (CGRU)-based method [14], or a temporal convolutional network (TCN)-based method [28]. In addition, random forest (RF)-based machine learning methods have been used to estimate wave directions and periods [29].…”