Research on the Extraction and Recognition of Space-Time-Frequency Features for Underwater Moving Targets

LIU Xiaochun; YANG Yunchuan; HU Youfeng; WANG Chenyu; LI Yongsheng

doi:10.11993/j.issn.2096-3920.2025-0067

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Article Navigation > Journal of Unmanned Undersea Systems > 2025 > Accepted Manuscript

LIU Xiaochun, YANG Yunchuan, HU Youfeng, WANG Chenyu, LI Yongsheng. Research on the Extraction and Recognition of Space-Time-Frequency Features for Underwater Moving Targets[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2025-0067

Citation:

LIU Xiaochun, YANG Yunchuan, HU Youfeng, WANG Chenyu, LI Yongsheng. Research on the Extraction and Recognition of Space-Time-Frequency Features for Underwater Moving Targets[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2025-0067

Citation:

LIU Xiaochun, YANG Yunchuan, HU Youfeng, WANG Chenyu, LI Yongsheng. Research on the Extraction and Recognition of Space-Time-Frequency Features for Underwater Moving Targets[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2025-0067

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Research on the Extraction and Recognition of Space-Time-Frequency Features for Underwater Moving Targets

doi: 10.11993/j.issn.2096-3920.2025-0067

1.
The 705 Research Institute, China Shipbuilding Industry Corporation, Xi’an 710077, China
2.
The Kunming Branch of 705 Research Institute, China Shipbuilding Industry Corporation, Kunming 650102, China

Received Date: 2025-05-16
Accepted Date: 2025-06-13
Rev Recd Date: 2025-06-13

Available Online: 2025-09-12

Abstract

Abstract

Aiming at the issue of inadequate bearing-angle adaptability in active sonar target recognition, this paper elaborates on the physical mechanism of active sonar target information perception from wave equation theory. Based on generalized multiple signal classification(MUSIC) spatial spectrum estimation, a novel method is proposed for acquiring the pseudo three-dimensional spatial feature of underwater targets by incorporating distance information, thereby effectively enhancing the adaptability of spatial features across different bearing angles. Additionally, research is conducted on methods to enhance Pseudo Wigner-Ville Distribution(PWVD) time-frequency features and extract Doppler frequency shift distribution features of moving targets. By leveraging the complementary advantages of these two algorithms, the bearing-angle adaptability is further improved. To address the challenge of scarce and imbalanced underwater target samples, the concept of meta-learning is integrated to construct a data-level fusion target recognition network that incorporates spatial, time-frequency, and Doppler domain features. The network is trained and tested using simulation and experimental data. The results demonstrate that the fusion features significantly improve the bearing-angle adaptability and anti-interference capability, providing a novel approach for the development of intelligent underwater target recognition technology.
- underwater target recognition,
- information fusion,
- multidimensional feature extraction,
- active sonar

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References(26)

References

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