水下无人系统学报2026，Vol.34Issue(3)：408-421,14.DOI:10.11993/j.issn.2096-3920.2026-0042
水下慢速小目标声学识别方法发展现状与展望
Development Status and Prospects of Acoustic Recognition Methods for Underwater Low-Speed Small Targets
摘要
Abstract
Underwater low-speed small targets,represented by divers and unmanned undersea vehicles,have become major threats to nearshore military and economic facilities due to their strong concealment,high maneuverability,and significant destructive potential.Their recognition has emerged as a hot topic and a challenging issue in the field of underwater security.This paper focused on three key aspects of acoustic recognition for underwater low-speed small targets:acoustic signal characteristic analysis,feature extraction,and feature classification.It systematically reviewed the current research status,core challenges,and development trends in this field.First,the acoustic signal characteristics of underwater low-speed small targets were analyzed from the perspectives of active echo signals and passive radiated noise.Subsequently,mainstream feature extraction methods were summarized based on active and passive features.Then,two major classification approaches,namely statistical learning and deep learning,were introduced and compared.Following this,the main challenges faced in this field and corresponding countermeasures were discussed.Finally,in light of technological development trends,future research directions were prospected,aiming to provide references for the advancement of underwater low-speed small target recognition technologies.关键词
水下慢速小目标/声学识别/特征提取/统计学习/深度学习Key words
underwater low-speed small target/acoustic recognition/feature extraction/statistical learning/deep learning分类
军事科技引用本文复制引用
刘雄厚,赖凯,杨益新..水下慢速小目标声学识别方法发展现状与展望[J].水下无人系统学报,2026,34(3):408-421,14.基金项目
国家自然科学基金项目(U2341203,12274346),国家重点研发计划项目(2016YFC1400200). （U2341203,12274346）
