相似网络构建与表征的水下声信号检测  

Underwater Acoustic Signal Detection using Similarity Network Construction and Representation

作　　者：张红伟 王海燕[2,3] 闫永胜[1,2] 申晓红[1,2] ZHANG Hongwei;WANG Haiyan;YAN Yongsheng;SHEN Xiaohong(School of Marine Science and Technology,Northwestern Polytechnical University,Xi’an 710077,China;Key Laboratory of Ocean Acoustics and Sensing(Northwestern Polytechnical University),Ministry of Industry and Information Technology,Xi’an 710072,China;School of Electronic Information and Artificial Intelligence Shaanxi University of Science and Technology,Xi’an 710021,China)

机构地区：[1]西北工业大学航海学院,西安710077 [2]海洋声学信息感知工业和信息化部重点实验室(西北工业大学),西安710072 [3]陕西科技大学电子信息与人工智能学院,西安710021

出　　处：《电子与信息学报》2024年第1期58-66,共9页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(62031021,62271404,62201439);西北工业大学2023研究生创新基金(CX2023041)。

摘　　要：水下声信号检测在海洋防御系统中扮演着不可或缺的角色,同时也广泛应用于民用领域。然而,在没有目标信号先验信息的情况下,目前仍缺乏行之有效的水下声信号检测方法。为此,该文提出了一种新的算法—相似网络,以解决在复杂海洋背景下水下目标检测的难题。该方法结合了信息几何和复杂网络理论,通过将节点相似度度量问题转化为矩阵流形上的几何问题,测量不同时间尺度上数据之间的相似性,并构建时间序列数据的网络表示。同时还引入了图信号处理理论,以提取目标信号内部隐藏的动力学特性,从而实现无目标先验信息下的水下声信号检测。通过对仿真和实测数据的研究验证,证明了该方法的有效性。结果表明,相似网络方法优于现有的网络构建和目标信号被动检测方法,能够更有效地检测水下声信号,实现无目标先验信息下的水下声信号检测。Underwater acoustic signal detection plays a crucial role in ocean defense systems and has broad applications in civilian domains.However,contemporary underwater acoustic signal detection methods need to be improved for effectiveness when prior information about the target is unavailable.This paper proposes a new algorithm-a similarity network-to address the challenge of underwater target detection in complex oceanic backgrounds.In this method,information geometry and complex network theory are combined,and the problem of measuring node similarity is converted into a geometric problem on a matrix manifold,wherein the similarity between data at different time scales is determined,and a network representation of the time series data is achieved.Concurrently,a graph signal processing theory is introduced to extract the hidden dynamic characteristics of the target signal,thereby achieving underwater acoustic signal detection without prior target information.Further,the effectiveness of this method is demonstrated through research and verification of the simulated and actual.Our results show that the similarity network method is superior to existing network construction and passive target detection methods,can detect underwater acoustic signals more effectively,and can achieve underwater acoustic signal detection without any prior target information.

关 键 词：复杂网络 信息几何 相似网络 声信号检测 

分 类 号：TN911.23[电子电信—通信与信息系统]