Ship Wake Detection Based on One-Dimensional Convolutional Neural Network

Abstract

In order to improve the detection accuracy of ship wake, this paper proposed a ship wake detection method based on a one-dimensional convolutional neural network (1DCNN). Firstly, the simulation data set was constructed by using the ship wake scattering echo model. Then the reliability of the scattering echo model was verified by the water tank simulation experiment, and the experimental data set was constructed. Finally, a 1DCNN was built by comprehensively considering the detection accuracy and parameter quantity of different structural models and compared with the traditional detection algorithm (based on a one-class support vector machine and back propagation neural network) on the data set. The simulation results show that compared with the traditional detection algorithm, the 1DCNN proposed in this paper improves the detection accuracy and detection efficiency of ship wake under different signal-to-noise ratios and has good engineering application value.