基于占空比特征的高频水声信号粗分类方法  

A Rough Classification Method for High Frequency Underwater Acoustic Signals Based on Duty Cycle Features

作　　者：张地 张松 李旭[1] 李晋[1] 王志欣 王大宇[1] ZHANG Di;ZHANG Song;LI Xu;LI Jin;WANG Zhixin;WANG Dayu(No.54 Institute of CETC,Shijiazhuang Hebei 050081,China)

机构地区：[1]中国电子科技集团公司第五十四研究所,河北石家庄050081

出　　处：《通信技术》2024年第6期545-550,共6页Communications Technology

基　　金：国家自然科学基金(U20B2071)。

摘　　要：高频水声信号主要包含水声通信信号和主动声呐信号,频带范围通常在3~40 kHz之间,具有信噪比高、隐含信息丰富等特点。图像识别和机器学习类方法受无人平台能量供给限制,难以实现工程应用。针对测距类主动声呐信号与水声通信信号低复杂度分类问题,提出了一种基于占空比特征的高频水声信号粗分类方法,利用水声通信信号和主动声呐信号占空比差异实现两类高频水声信号粗分类。最后,通过仿真信号和实测数据验证了算法的有效性。High frequency underwater acoustic signals mainly include underwater acoustic communication signals and active sonar signals,and the frequency band range is usually between 3 kHz to 40 kHz,which is characterized by high signal-to-noise ratio and rich hidden information.Methods such as image recognition and machine learning are limited by the energy supply of unmanned platforms,making it difficult to achieve engineering applications.Aiming at the low-complexity classification problem of active sonar signals and underwater acoustic communication signals in the ranging class,a rough classification method for high-frequency underwater acoustic signals based on duty cycle characteristics is proposed,which utilizes the difference in duty cycles of underwater acoustic communication signals and active sonar signals to achieve the rough classification of two classes of high-frequency underwater acoustic signals.Finally,the effectiveness of the algorithm is verified by simulated signals and measured data.

关 键 词：水声通信 主动声呐 信号粗分类 占空比 

分 类 号：TN929.3[电子电信—通信与信息系统]