Page 193 - 应用声学2019年第4期

第 38 卷 第 4 期 Vol. 38, No. 4
2019 年 7 月 Journal of Applied Acoustics July, 2019

⋄ 李启虎院士八十华诞学术论文 ⋄

水声被动目标识别技术挑战与展望

程玉胜 邱家兴 刘 振 † 李海涛

(海军潜艇学院 青岛 266071)

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
中图法分类号: O429 文献标识码: A 文章编号: 1000-310X(2019)04-0653-07
DOI: 10.11684/j.issn.1000-310X.2019.04.023

Challenges and prospects of underwater acoustic passive
target recognition technology

CHENG Yusheng QIU Jiaxing LIU Zhen LI Haitao

(Navy Submarine Academy, Qingdao 266071, China)

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.
Key words Passive sonar target recognition, Underwater acoustic low frequency detection, Ship vibration
and noise reduction, Deep learning, Recognition characteristics

2019-02-22 收稿; 2019-05-07 定稿
作者简介: 程玉胜 (1963- ), 男, 安徽桐城人, 博士, 教授, 研究方向: 水声目标识别。
† 通讯作者 E-mail: liuzhen_lzz@163.com