Distinguishing multiple surface ships using one acoustic vector sensor based on a convolutional neural network.

Journal: JASA express letters
Published Date:

Abstract

A direction of arrival (DOA) estimation method based on a convolutional neural network (CNN) using an acoustic vector sensor is proposed to distinguish multiple surface ships in a selected frequency band. The cross-spectrum of the pressure and particle velocity are provided as inputs to the CNN, which is trained using data obtained by employing an acoustic propagation model under different environmental and source parameters. By learning the characteristics of acoustic propagation, the multisource distinguishing performance of the CNN is improved. The proposed method is experimentally validated using real data.

Authors

  • Huaigang Cao
    Hangzhou Applied Acoustics Research Institute, Hangzhou, Zhejiang 310023, China.
  • Qunyan Ren
    Key Laboratory of Underwater Acoustic Environment, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China.