| 张少康,田德艳.水下声目标的梅尔倒谱系数智能分类方法[J].,2019,38(2):267-272 |
| 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 |
| 投稿时间：2018-09-05 修订日期：2019-03-01 |
| 中文摘要: |
| 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（MFCC）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（LSTM）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。 |
| 英文摘要: |
| 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 Cepstrum coefficient (MFCC) is proposed. By extracting the features of Mel 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 cepstrum coefficient can identify the target noise without relying on the artificial feature extraction and have an intelligent recognition ability. |
| DOI：10.11684/j.issn.1000-310X.2019.02.017 |
| 中文关键词: 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 |
| 英文关键词: Underwater acoustic targets classification, Mel cepstrum, Long short-term memory network, Intelligent classification |
| 基金项目: |
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