Underwater Low-speed Small Target Recognition: A Comprehensive Overview and Prospects

LIU Xionghou; LAI Kai; YANG Yixin

doi:10.11993/j.issn.2096-3920.2026-0042

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Article Navigation > Journal of Unmanned Undersea Systems > 2026 > Accepted Manuscript

LIU Xionghou, LAI Kai, YANG Yixin. Underwater Low-speed Small Target Recognition: A Comprehensive Overview and Prospects[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2026-0042

Citation:

LIU Xionghou, LAI Kai, YANG Yixin. Underwater Low-speed Small Target Recognition: A Comprehensive Overview and Prospects[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2026-0042

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Underwater Low-speed Small Target Recognition: A Comprehensive Overview and Prospects

doi: 10.11993/j.issn.2096-3920.2026-0042

LIU Xionghou^{1, 2, 3
,
,},
LAI Kai^{1, 2, 3
,},
YANG Yixin^4
,

1.
School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710129, China
2.
Shaanxi Key Laboratory of Underwater Information Technology, Xi’an 710072, China
3.
Hanjiang National Laboratory, Wuhan 430061, China
4.
School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

Received Date: 2026-03-04
Accepted Date: 2026-03-27
Rev Recd Date: 2026-03-22

Available Online: 2026-05-10

Abstract

Abstract

Underwater low-speed small targets, represented by frogmen and unmanned underwater vehicles, have become major threats to nearshore military and economic facilities due to their strong concealment, high maneuverability, and significant destructive potential. Their recognition has emerged as a hot topic and a challenging issue in the field of underwater security. This paper focuses on three key aspects of acoustic recognition for underwater low-speed small targets: acoustic signal characteristic analysis, feature extraction, and feature classification. It systematically reviews the current research status, core challenges, and development trends in this field. First, the acoustic signal characteristics of underwater low-speed small targets are analyzed from the perspectives of active echo signals and passive radiated noise. Subsequently, mainstream feature extraction methods are summarized based on active and passive features. Then, two major classification approaches—statistical learning and deep learning—are introduced and compared. Following this, the main challenges faced in this field and corresponding countermeasures are discussed. Finally, in light of technological development trends, future research directions are prospected, aiming to provide references for the advancement of underwater low-speed small target recognition technologies.
- Underwater low-speed small target,
- Classification and recognition,
- Feature extraction

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References(121)

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