声呐图像水下目标识别综述与展望  

Sonar Image Underwater Target Recognition:A Comprehensive Overview and Prospects

作　　者：黄海宁[1,2,3] 李宝奇 刘纪元 刘正君[1,2] 韦琳哲 赵爽 HUANG Haining;LI Baoqi;LIU Jiyuan;LIU Zhengjun;WEI Linzhe;ZHAO Shuang(Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190,China;Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing,Chinese Academy of Sciences,Beijing 100190,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院声学研究所,北京100190 [2]中国科学院先进水下信息技术重点实验室,北京100190 [3]中国科学院大学,北京100049

出　　处：《电子与信息学报》2024年第5期1742-1760,共19页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(11904386);国家基础科研计划重大项目(JCKY2016206A003);中国科学院青年创新促进会(2019023)。

摘　　要：随着海洋资源开发和水下作业的增加,声呐图像水下目标识别已成为热门研究领域。该文全面回顾了该领域的现状和未来趋势。首先,强调了声呐图像水下目标识别的背景和重要性,指出水下环境复杂和样本稀缺增加了任务难度。其次,深入探讨了典型的成像声呐技术,包括前视声呐、侧扫声呐、合成孔径声呐、多波束测深仪、干涉合成孔径声呐和前视三维声呐等。接下来,系统地审视了二维和三维声呐图像水下目标识别方法,比较了不同算法的优劣,还讨论了声呐图像序列的关联识别方法。最后,总结了当前领域的主要挑战,展望了未来研究方向,旨在促进水下声呐目标识别领域的发展。With the increasing development of marine resources and underwater operations,sonar image-based underwater target recognition has become a hot research area.This article provides a comprehensive review of the current status and future trends in this field.Initially,the background and significance of sonar imagebased underwater target recognition are emphasized,noting that the complexity of the underwater environment and the scarcity of samples increase the task difficulty.Subsequently,typical imaging sonar technologies are delved,including forward-looking sonar,side-scan sonar,synthetic aperture sonar,multibeam echo sounder,interferometric synthetic aperture sonar,and forward-looking 3D sonar.Following that,2D and 3D sonar image-based underwater target recognition methods are systematically examined,the strengths and weaknesses of different algorithms are compared,and methods for the correlated recognition of sonar image sequences are discussed.Finally,the major challenges in the current field and future research directions are summarized,aiming to foster the development of the underwater sonar target recognition field.

关 键 词：声呐图像目标识别 深度学习 合成孔径声呐 前视三维声呐 目标识别 

分 类 号：TN929.3[电子电信—通信与信息系统] TP391[电子电信—信息与通信工程]