哈尔滨工程大学学报2026，Vol.47Issue(4)：778-786,9.DOI:10.11990/jheu.202411021
基于听觉注意脑电信号特征的水声目标识别方法
Underwater target recognition based on auditory electroencephalogram features
摘要
Abstract
To address the challenges in accurate underwater target recognition and leverage the advantages of hu-man auditory perception in handling target recognition tasks in complex environments,an approach utilizing audi-tory electroencephalogram(EEG)signals evoked by underwater acoustic targets is proposed.Experimental re-sults demonstrate that the ECA-CNN network model based on a channel attention mechanism achieves a recognition rate of 94.35%for EEG signals elicited by four types of ship radiated noise,significantly outperforming methods such as Riemannian manifolds and support vector machines.This indicates that auditory attention EEG features can effectively identify underwater acoustic targets.Moreover,by incorporating insights from neuroscience re-search,the feature extraction results of the channel attention mechanism are interpreted,enriching the interpret-ability of deep learning methods.关键词
水声目标识别/听觉注意/脑电信号/奇异谱分析/黎曼流形/支持向量机/通道注意力机制/卷积神经网络Key words
underwater target recognition/auditory attention/electroencephalogram/singular spectrum analysis/riemannian manifold/support vector machine/channel attention mechanism/convolutional neural network分类
信息技术与安全科学引用本文复制引用
纳子涵,曾向阳..基于听觉注意脑电信号特征的水声目标识别方法[J].哈尔滨工程大学学报,2026,47(4):778-786,9.基金项目
国家自然科学基金项目(52271351). （52271351）
