水下无人系统学报2023，Vol.31Issue(6)：839-846,8.DOI:10.11993/j.issn.2096-3920.2022-0052
基于一维卷积神经网络的舰船尾流检测
Ship Wake Detection Based on One-Dimensional Convolutional Neural Network
摘要
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.关键词
舰船尾流检测/一维卷积神经网络/单分类支持向量机/反向传播神经网络Key words
ship wake detection/one-dimensional convolutional neural network/one-class support vector machine/back propagation neural network分类
军事科技引用本文复制引用
杨长生,苟文博,梁红..基于一维卷积神经网络的舰船尾流检测[J].水下无人系统学报,2023,31(6):839-846,8.基金项目
国家自然科学基金项目资助(61771398,61971354). （61771398,61971354）
