A Review of Underwater Target Recognition Based on Passive Sonar Acoustic Signals
Underwater target recognition based on passive sonar acoustic signals is a significant technical challenge in the field of underwater unmanned detection,with broad applications in both military and civilian domains.This paper provides a comprehensive exposition of the methodology and process involved in underwater target recogni-tion using passive sonar acoustic signals,addressing data processing and recognition methods at two levels.Regard-ing data processing,this paper presents a thorough exploration of the fundamental principles of passive sonar signal processing from three key aspects:The underlying process of underwater target recognition based on passive sonar signals,the mathematical foundations of passive sonar acoustic signal analysis,and the extraction of relevant fea-tures.At the level of recognition methods,this paper offers a comprehensive analysis of underwater target recogni-tion techniques based on machine learning algorithms,and focus on the research conducted with deep learning al-gorithms at its core.The paper systematically summarizes and analyzes the current research progress across vari-ous learning paradigms,including supervised learning,unsupervised learning and self-supervised learning,and ana-lyzes their advantages and disadvantages in terms of the algorithm's labeled data requirement,robustness,scalabil-ity and adaptability.Additionally,this paper provides an overview of widely-used public datasets in the field,and outlines the essential elements that such datasets should possess.Finally,by discussing the process of underwater target recognition,this paper summarizes the current difficulties and challenges in automatic underwater target re-cognition algorithms based on passive sonar acoustic signals,and offers insights into the future development direc-tion of this field.
万方数据
维普
