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DONG Xinxin, ZHANG Zhexuan, ZHANG Weiye. Research Status and Development Trends of Foreign Submarine Detection Technologies[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2025-0133
Citation: DONG Xinxin, ZHANG Zhexuan, ZHANG Weiye. Research Status and Development Trends of Foreign Submarine Detection Technologies[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2025-0133

Research Status and Development Trends of Foreign Submarine Detection Technologies

doi: 10.11993/j.issn.2096-3920.2025-0133
  • Received Date: 2025-09-25
  • Accepted Date: 2025-11-06
  • Rev Recd Date: 2025-11-01
  • Available Online: 2026-03-10
  • The primary threat of submarines stems from their concealment. In recent years, with the advancement of submarine noise reduction technologies and the intensification of electronic countermeasures, enhancing submarine detection methods and capabilities has become increasingly urgent. This paper reviews the operational characteristics (including noise, magnetic field, wake, and gravitational field) and typical combat modes of submarines, expounds on the advantages and limitations of different anti-submarine platforms and detection approaches, and summarizes the development status of detection methods (such as acoustic detection and magnetic anomaly detection) as well as representative foreign models. It analyzes the key technologies for submarine detection from three aspects: anti-jamming capability, real-time data processing and information fusion, and unmanned system collaboration and autonomous decision-making. The analysis indicates that the integration of new-type detection means with multi-source information fusion can effectively improve detection performance, while the development of capabilities like unmanned system collaboration and autonomous decision-making may serve as a breakthrough for the transformation of anti-submarine modes. This study provides valuable references for future research and development efforts in the field of submarine detection.

     

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