面向无人机群目标探测架构和关键技术研究进展
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1.南京航空航天大学,电磁频谱空间动态认知系统工信部重点实验室,江苏 南京 211106;2.南京航空航天大学,电子信息工程学院,江苏 南京 211106

作者简介:

张小飞(1977-),男,博士,教授,博士生导师,主要研究方向为移动通信、阵列信号处理、通信信号处理.email:zhangxiaofei@nuaa.edu.cn.
王斌(2000-),男,在读硕士研究生,主要研究方向为阵列信号处理.
孙萌(1988-),男,博士,副教授,主要研究方向为阵列信号处理、频谱分析、干扰源定位、机器学习、智能优化算法.
吴启晖(1970-),男,博士,教授,博士生导师,主要研究方向为认知科学与应用、认知信息论、天地一体化智能信息网络、电磁空间频谱认知智能管控、无人机认知集群.

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Research progress on detection architecture and key technologies for UAV swarm targets
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Affiliation:

1.Key Laboratory of Spatial Dynamic Cognitive System of Electromagnetic Spectrum, Nanjing University of Aeronautics and Astronautics,Nanjing Jiangsu 211106,China;2.School of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics,Nanjing Jiangsu 211106,China

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    摘要:

    无人机(UAV)在军事、商业和民用领域的应用日益广泛,随着无人机群数量的增加,对于安全、隐私和公共利益的影响也日益受到重视。因此,研究面向无人机群目标的探测技术显得越来越重要。目前国内外已经开展了多项无人机群目标的探测相关研究工作。本文研究了无人机群目标探测的研究现状以及面临的挑战;然后针对这些挑战讨论了无人机群目标探测架构技术的类型。针对集中式、单一手段难以满足无人机群精细化感知、态势评估需求,提供了面向无人机群目标的空地联合多域探测架构,该架构具体包括:组网雷达、分布式频谱被动监测设备、移动多光谱感知设备、移动频谱监测设备;结合了不同感知方式在不同距离、不同方位、不同粒度等维度的优势,通过级联、协同、融合方式突破了单域探测的局限性。最后对其中关键技术进行了分析与总结。

    Abstract:

    Unmanned Aerial Vehicles(UAV) are increasingly widely used in military, commercial and civil fields. With the increase of the number of Guavas, the impact on security, privacy and public interests has also been increasingly valued. Therefore, it is more and more important to study the target detection technology for UAV group. At present, a number of research work related to the detection of UAV swarm targets has been carried out at home and abroad. In this paper, the research status and challenges of UAV group target detection are studied. Then, aiming at these challenges, the types of UAV group target detection architecture technology are discussed. In view of the difficulty of centralized and single means to meet the needs of UAV group fine perception and situation assessment, the air-ground joint multi-domain detection architecture for UAV group targets is provided, which specifically includes networking radar, distributed spectrum passive monitoring equipment, mobile multi-spectral sensing equipment, mobile spectrum monitoring equipment. Combining the advantages of different sensing methods in different distances, different directions, different granularity and other dimensions, it breaks through the limitations of single-domain detection through cascade, collaboration and fusion. Finally, the key technologies are analyzed and summarized.

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张小飞,王斌,孙萌,吴启晖.面向无人机群目标探测架构和关键技术研究进展[J].太赫兹科学与电子信息学报,2023,21(4):539~554

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  • 收稿日期:2023-02-14
  • 最后修改日期:2023-03-12
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  • 在线发布日期: 2023-05-29
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