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  • 标题:An Underwater Acoustic Target Recognition Method Based on Spectrograms with Different Resolutions
  • 本地全文:下载
  • 作者:Xinwei Luo ; Minghong Zhang ; Ting Liu
  • 期刊名称:Journal of Marine Science and Engineering
  • 电子版ISSN:2077-1312
  • 出版年度:2021
  • 卷号:9
  • 期号:11
  • 页码:1246
  • DOI:10.3390/jmse9111246
  • 语种:English
  • 出版社:MDPI AG
  • 摘要:This paper focuses on the automatic target recognition (ATR) method based on ship-radiated noise and proposes an underwater acoustic target recognition (UATR) method based on ResNet. In the proposed method, a multi-window spectral analysis (MWSA) method is used to solve the difficulty that the traditional time–frequency (T–F) analysis method has in extracting multiple signal characteristics simultaneously. MWSA generates spectrograms with different T–F resolutions through multiple window processing to provide input for the classifier. Because of the insufficient number of ship-radiated noise samples, a conditional deep convolutional generative adversarial network (cDCGAN) model was designed for high-quality data augmentation. Experimental results on real ship-radiated noise show that the proposed UATR method has good classification performance.
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