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水声被动目标识别技术挑战与展望
引用本文:程玉胜,邱家兴,刘振,李海涛.水声被动目标识别技术挑战与展望[J].应用声学,2019,38(4):653-659.
作者姓名:程玉胜  邱家兴  刘振  李海涛
作者单位:海军潜艇学院,海军潜艇学院,海军潜艇学院,海军潜艇学院
摘    要:低频水声探测和船舶减振降噪技术发展,使得传统水声目标识别技术性能逐渐下降。该文分析了声呐工作带宽、探测频率、船舶减振降噪给识别技术带来的挑战。针对低频声呐广泛使用的低频线谱识别,研究了低频线谱的识别能力问题;针对智能识别技术发展,研究了深度学习技术在船舶辐射噪声识别中的应用问题,并给出了数据试验结果,文章最后指出了水声被动目标识别技术亟需开展的研究内容和方向。

关 键 词:被动声呐识别,水声低频探测,船舶减振降噪,深度学习,识别特性
收稿时间:2019/2/22 0:00:00
修稿时间:2019/7/3 0:00:00

Challenge and prospects of underwater acoustic passive target recognition technology
Cheng Yusheng,QIU Jiaxing,Liu Zhen and Li Haitao.Challenge and prospects of underwater acoustic passive target recognition technology[J].Applied Acoustics,2019,38(4):653-659.
Authors:Cheng Yusheng  QIU Jiaxing  Liu Zhen and Li Haitao
Institution:Navy Submarine Academy,Navy Submarine Academy,Navy Submarine Academy,Navy Submarine Academy
Abstract:With the development of low frequency underwater acoustic detection and the technology of ship vibration and noise reduction, the performance of traditional underwater acoustic target recognition technology is gradually declining. This paper analyses the challenges brought by sonar bandwidth, detection frequency, ship vibration and noise reduction to identification technology. Aiming at the recognition of low frequency line spectrum widely used in low frequency sonar, the recognition ability of low frequency line spectrum is studied. Aiming at the development of intelligent recognition technology, the application of deep learning technology in the recognition of ship radiated noise is studied, and the data test results are given. Finally, the contents and directions of the research on underwater acoustic passive target recognition technology are pointed out.
Keywords:Passive sonar target recognition  Underwater acoustic low frequency detection  Ship vibration and noise reduction  Deep learning  Recognition characteristics
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