海上跨域集群水下目标协同追踪: 关键技术与展望

李一辰; 关新平; 黄沛烁; 王布依祎; 杨紫雯; 于文彬

doi:10.16383/j.aas.c250309

海上跨域集群水下目标协同追踪: 关键技术与展望

doi: 10.16383/j.aas.c250309 cstr: 32138.14.j.aas.c250309

李一辰^{1, 2, 3,},
关新平^{1, 2, 3,},
黄沛烁^{1, 2, 3,},
王布依祎^{1, 2, 3,},
杨紫雯^{1, 2, 3,},
于文彬^{1, 2, 3,}

1.
上海交通大学自动化与感知学院上海 200240
2.
海底科学与划界全国重点实验室上海 200240
3.
系统控制与信息处理教育部重点实验室上海 200240

基金项目: 国家自然科学基金(62203299, 62373246), 上海交通大学深蓝计划(SL2023MS007), 深海载人装备全国重点实验室基金(2024SKLDMV04)资助

详细信息

作者简介:
李一辰：上海交通大学自动化与感知学院助理研究员. 主要研究方向为多潜器协同定位, 水下无线网络, 多源信息融合. E-mail: liyichensjtu@sjtu.edu.cn

关新平：上海交通大学自动化与感知学院教授. 主要研究方向为工业信息物理系统, 无线组网及应用, 水下传感器网络. E-mail: xpguan@sjtu.edu.cn

黄沛烁：上海交通大学自动化与感知学院博士后. 主要研究方向为水下机器人, 多潜器协同路径规划. E-mail: huangpeishuo@sjtu.edu.cn

王布依祎：上海交通大学自动化与感知学院博士研究生. 主要研究方向为水声通信, 水下无线网络. E-mail: byywangsjtu@163.com

杨紫雯：上海交通大学自动化与感知学院长聘教轨副教授. 主要研究方向为多智能体感知, 多智能体编队控制, 感知控制联合设计. E-mail: 1106385445@sjtu.edu.cn

于文彬：上海交通大学自动化与感知学院副研究员. 主要研究方向为水下网络的信号处理和复合测量. 本文通信作者. E-mail: yuwenbin@sjtu.edu.cn

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- 被引次数: 0
出版历程
- 收稿日期: 2025-07-10
- 录用日期: 2025-10-09
- 网络出版日期: 2025-12-01
- 刊出日期: 2026-01-29

Underwater Cooperative Target Tracking Using Maritime Cross-Domain Swarms: Key Technologies and Future Perspectives

LI Yi-Chen^{1, 2, 3
,},
GUAN Xin-Ping^{1, 2, 3
,},
HUANG Pei-Shuo^{1, 2, 3
,},
WANG Bu-Yi-Yi^{1, 2, 3
,},
YANG Zi-Wen^{1, 2, 3
,},
YU Wen-Bin^{1, 2, 3
,}

1.
School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240
2.
National Key Laboratory of Underwater Science and Delimitation, Shanghai 200240
3.
Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai 200240

Funds: Supported by National Natural Science Foundation of China (62203299, 62373246), Oceanic Interdisciplinary Program of Shanghai Jiao Tong University (SL2023MS007), and Research Fund of State Key Laboratory of Deep-Sea Manned Vehicles (2024SKLDMV04)

More Information

Author Bio:
LI Yi-Chen　Assistant researcher at the School of Automation and Intelligent Sensing, Shanghai Jiao Tong University. His research interests include multi-AUV cooperative localization, underwater wireless networks, and multi-source information fusion

GUAN Xin-Ping　Professor at the School of Automation and Intelligent Sensing, Shanghai Jiao Tong University. His research interests include industrial cyber-physical systems, wireless networking and applications, and underwater sensor networks

HUANG Pei-Shuo　Postdoctor at the School of Automation and Intelligent Sensing, Shanghai Jiao Tong University. His research interests include underwater robotics and multi-AUV cooperative trajectory planning

WANG Bu-Yi-Yi　Ph.D. candidate at the School of Automation and Intelligent Sensing, Shanghai Jiao Tong University. Her research interests include acoustic communication and underwater wireless networks

YANG Zi-Wen　Tenure track associate professor at the School of Automation and Intelligent Sensing, Shanghai Jiao Tong University. Her research interests include multi-agent perception, multi-agent formation control, and the co-design of perception and control

YU Wen-Bin　Associate researcher at the School of Automation and Intelligent Sensing, Shanghai Jiao Tong University. His research interests include signal processing and composite measurement for underwater networks. Corresponding author of this paper

摘要

摘要: 随着海洋开发不断推进, 水下目标追踪作为无人集群实现对作业目标持续接近的基础性技术, 在海上搜救、海洋监测、海底资源勘探等关键应用中发挥着重要作用. 同时, 海上跨域集群通过无人机、无人船与无人潜器等异构平台间的信息交互与自主协同, 能够在复杂海洋环境中实现对水下目标的高效探测与持续追踪, 相比单一水下域集群, 其在感知与作业能力的提升等方面具有巨大的潜力. 然而, 当前水下协同追踪技术仍存在感知测量能力不足、跨域协同机制不完善和环境适应性难以兼顾等挑战. 为此, 本文首先针对水下目标追踪的发展趋势进行分析; 同时, 面向追踪过程中定位、跟踪、通信与规划四个基础模块, 总结研究难点和挑战, 并梳理国内外研究进展; 最后, 针对联合设计等新颖的研究理念和前沿需求进行探讨, 以期为海上跨域集群水下目标追踪技术的发展提供参考.
- 跨域集群 /
- 水下目标 /
- 协同追踪 /
- 趋势分析 /
- 联合设计
Abstract: With the continuous advancement of marine development, underwater target tracking, as a foundational technology, enables continuous navigation of unmanned swarms toward the target and plays a crucial role in various applications such as maritime search and rescue, ocean monitoring, and seabed resource exploration. Meanwhile, maritime cross-domain swarms composed of heterogeneous platforms, including unmanned aerial, surface, and underwater vehicles, demonstrate significant potential in achieving efficient detection and tracking of underwater targets through information interaction and autonomous cooperation, which, compared to underwater single-domain swarms, holds significant potential for improving the effectiveness of perception and operation in complex marine environments. However, current technologies still face challenges including insufficient sensing capabilities, immature cross-domain cooperation mechanisms, and compromised environmental adaptability. To address these issues, this paper first analyzes the development trends of underwater target tracking. Subsequently, focusing on four fundamental modules, localization, tracking, communcation, and planning, we summarize existing research difficulties and review domestic as well as international research progress. Finally, emerging concepts, such as co-design, and frontier requirements are discussed, aiming to provide references for advancing underwater cooperative target tracking technologies with cross-domain swarms.
- cross-domain swarms /
- underwater target /
- cooperative tracking /
- trend analysis /
- co-design

HTML全文

图 1 海上跨域集群水下目标协同追踪

Fig. 1 Cooperative underwater target tracking using maritime cross-domain swarms

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图 2 基线定位系统

Fig. 2 Baseline positioning systems

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图 3 声光融合机制

Fig. 3 Acoustic-optical fusion strategy

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图 4 跨域通信网络

Fig. 4 Cross-domain communication networks

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图 5 OCDM发送信号时频图^[75−76]

Fig. 5 Time-frequency diagram of OCDM signals^[75−76]

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图 6 基于信息熵的动态路径规划

Fig. 6 Dynamic trajectory planning based on information entropy

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图 7 基于传感器选择的路径规划^[90]

Fig. 7 Sensor selection-based trajectory planning^[90]

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图 8 联合设计思路

Fig. 8 The concept of co-design

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