水下声目标的梅尔倒谱系数智能分类方法  

Intelligent classification method of Mel frequency cepstrum coefficient for underwater acoustic targets

作　　者：张少康[1] 田德艳 ZHANG Shaokang;TIAN Deyan(Navy Submarine Academy,Qingdao 266000,China;National Laboratory for Marine Science and Technology,Qingdao 266000,China)

机构地区：[1]海军潜艇学院,青岛266000 [2]青岛海洋科学与技术试点国家实验室,青岛266000

出　　处：《应用声学》2019年第2期267-272,共6页Journal of Applied Acoustics

摘　　要：传统水下声目标识别分类方法具有较强的人机交互特性,无法满足未来水下无人平台智能识别分类水声目标的需求。针对这一问题,提出了一种基于梅尔倒谱系数的水下声目标智能识别分类方法,该方法通过提取水下声目标梅尔倒谱系数特征,采用长短时记忆网络构建了智能识别分类模型。使用实际水声信号对该方法进行了验证,结果表明,基于梅尔倒谱系数的水下声目标智能识别分类方法能够在不依赖人工提取特征的情况下,对目标噪声进行识别分类,具备智能化识别分类能力。The traditional methods of underwater target noise recognition have strong human-computer interaction characteristics,which can not meet the requirements of intelligent underwater acoustic target recognition for the future unmanned underwater platform.To solve this problem,an intelligent recognition method of underwater target noise based on Mel frequency cepstrum coefficient(MFCC)is proposed.By extracting the features of Mel frequency cepstrum coefficient,an intelligent recognition model is constructed by using long short-term memory network(LSTM).The underwater acoustic signal is used to verify the method.The results show that the method of underwater target noise intelligent recognition based on Mel frequency cepstrum coefficient can identify the target noise without relying on the artificial feature extraction and have an intelligent recognition ability.

关 键 词：水下声目标识别分类 梅尔倒谱系数 长短时记忆网络 智能分类 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]