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MmPiFNN:A multi-mode physics-informed fuzzy neural network for passive recognition of surface ships by underwater equipment using ship radiated noise signals

Feng Liu Zipeng Li Kunde Yang Fuhu Chen Junru Yu

防务技术2026，Vol.59Issue(5)：243-266,24.

防务技术2026，Vol.59Issue(5)：243-266,24.DOI:10.1016/j.dt.2025.11.003

MmPiFNN:A multi-mode physics-informed fuzzy neural network for passive recognition of surface ships by underwater equipment using ship radiated noise signals

Feng Liu ¹Zipeng Li ²Kunde Yang ²Fuhu Chen ³Junru Yu⁴

作者信息

1. School of Marine Science and Technology,Northwestern Polytechnical University,Xi'an,710072,China||Hanjiang National Laboratory,Wuhan,430060,China||Key Laboratory of Ocean Acoustics and Sensing(Northwestern Polytechnical University),Ministry of Industry and Information Technology,Xi'an,710072,China
2. Ocean Institute of Northwestern Polytechnical University,Taicang,215400,China||School of Marine Science and Technology,Northwestern Polytechnical University,Xi'an,710072,China||Key Laboratory of Ocean Acoustics and Sensing(Northwestern Polytechnical University),Ministry of Industry and Information Technology,Xi'an,710072,China
3. Hanjiang National Laboratory,Wuhan,430060,China
4. School of Marine Science and Technology,Northwestern Polytechnical University,Xi'an,710072,China
折叠

摘要

关键词

Ship radiated noise/Physical constraint/Mode fusion/Fuzzy system/Passive recognition

Key words

Ship radiated noise/Physical constraint/Mode fusion/Fuzzy system/Passive recognition

引用本文复制引用

Feng Liu,Zipeng Li,Kunde Yang,Fuhu Chen,Junru Yu..MmPiFNN:A multi-mode physics-informed fuzzy neural network for passive recognition of surface ships by underwater equipment using ship radiated noise signals[J].防务技术,2026,59(5):243-266,24.

基金项目

This work was supported by the Joint Training Fund Project of Hanjiang National Laboratory(Grant No.LP2024005),and the Key Program of the National Natural Science Foundation of China(Grant No.52231013),and the National Natural Science Founda-tion of China(Grant No.12427809),and the National Key R&D Program of China(2022YFC3101901),and the Northwestern Pol-ytechnical University Fund(D5000240072). （Grant No.LP2024005）

防务技术

ISSN：2214-9147

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