Wave height measurement based on feature fusion extracted from marine radar images

Obtaining wave information near the ship's location is not only crucial for ensuring navigation safety, but also an important basis for meteorological forecasting and disaster prevention, which is of great significance for marine engineering and scientific research. To further improve the estimation accuracy of significant wave height (SWH) from non-coherent X-band marine radar image, a wave height measurement method is proposed based on the feature fusion and radial basis function (RBF) network. The wave slope and signal-to-noise ratio (SNR) extracted from radar image and environmental factors such as wave direction and wind information are introduced to establish the feature vector as the input of RBF network. By training the RBF network model, accurate estimation of SWH is achieved. The measured radar data is used for experimental verification, and the experimental results show that the feature fusion method proposed has higher accuracy and reliability in calculating SWH than the shadow statistical method and the traditional SNR-based method, when the environmental factor of wind information and wave direction is considered. The correlation coefficient between buoy record and estimated SWH approaches 0.92, and the root mean square error deceases to 0.21 m.