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基于运动模型的低空非合作无人机目标识别

陈唯实 刘佳 陈小龙 李敬

陈唯实, 刘佳, 陈小龙, 等 . 基于运动模型的低空非合作无人机目标识别[J]. 北京航空航天大学学报, 2019, 45(4): 687-694. doi: 10.13700/j.bh.1001-5965.2018.0447
引用本文: 陈唯实, 刘佳, 陈小龙, 等 . 基于运动模型的低空非合作无人机目标识别[J]. 北京航空航天大学学报, 2019, 45(4): 687-694. doi: 10.13700/j.bh.1001-5965.2018.0447
CHEN Weishi, LIU Jia, CHEN Xiaolong, et al. Non-cooperative UAV target recognition in low-altitude airspace based on motion model[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(4): 687-694. doi: 10.13700/j.bh.1001-5965.2018.0447(in Chinese)
Citation: CHEN Weishi, LIU Jia, CHEN Xiaolong, et al. Non-cooperative UAV target recognition in low-altitude airspace based on motion model[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(4): 687-694. doi: 10.13700/j.bh.1001-5965.2018.0447(in Chinese)

基于运动模型的低空非合作无人机目标识别

doi: 10.13700/j.bh.1001-5965.2018.0447
基金项目: 

国家自然科学基金委员会-中国民用航空局民航联合研究基金 U1633122

国家重点研发计划 2016YFC0800406

详细信息
    作者简介:

    陈唯实 男, 高级工程师。主要研究方向:低空空域安全监视、雷达目标检测与跟踪、机场安全运行技术

    通讯作者:

    陈唯实, E-mail: chenwsh@mail.castc.org.cn

  • 中图分类号: TN959.1

Non-cooperative UAV target recognition in low-altitude airspace based on motion model

Funds: 

Joint Research Foundation of National Natural Science Foundation of China (NSFC) and Civil Aviation Administration of China (CAAC) U1633122

National Key R & D Program of China 2016YFC0800406

More Information
  • 摘要:

    为保障低空安全,在利用雷达数据探测无人机目标的同时剔除飞鸟等虚警信息,提出了一种基于运动模型的低空非合作无人机目标识别方法,作为已有目标跟踪方法应用的拓展。首先,建立多种运动模型模拟无人机和飞鸟目标运动;然后,基于多种运动模型进行目标跟踪,并估计各种运动模型的出现概率;最后,以各种运动模型在连续时间内出现概率的方差均值来度量目标运动模型的转换频率。通过对仿真数据和机场低空监视雷达实测数据的处理,所提方法能够在杂波环境中跟踪无人机目标并剔除飞鸟目标,进一步验证了其有效性和实用性。

     

  • 图 1  无人机与飞鸟目标识别方法流程

    Figure 1.  Flowchart of recognition method for UAV and flying bird targets

    图 2  无人机与飞鸟目标轨迹仿真轨迹

    Figure 2.  Simulated trajectories of UAV and flying bird targets

    图 3  无人机目标跟踪中的模型估计概率

    Figure 3.  Model estimation probability in UAV target tracking

    图 4  飞鸟目标跟踪中的模型估计概率

    Figure 4.  Model estimation probability in flying bird target tracking

    图 5  无人机目标识别的ROC曲线

    Figure 5.  ROC curves of UAV target recognition

    图 6  加入背景噪声的目标轨迹仿真

    Figure 6.  Simulated trajectories of targets with background clutters

    图 7  背景噪声环境中的无人机目标识别ROC曲线

    Figure 7.  ROC curves of UAV target recognition in background cluttered environment

    图 8  北海机场低空雷达监视数据

    Figure 8.  Low-altitude radar surveillance data at Beihai Airport

    图 9  无人机目标跟踪与识别结果示意图

    Figure 9.  Schematic of UAV target tracking and recognition results

    表  1  无人机与飞鸟目标的F均值

    Table  1.   Mean value of F of UAV and flying bird targets

    无人机 飞鸟
    p=0.2 p=0.3 p=0.4 p=0.5
    0.005 9 0.044 7 0.051 1 0.059 4 0.062 5
    下载: 导出CSV

    表  2  无人机目标识别结果

    Table  2.   UAV target recognition results

    S 无人机目标 其他低空目标
    0.005 1 0
    0.01 1 2
    0.02 1 2
    0.03 1 5
    0.04 1 6
    0.05 1 7
    0.06 1 10
    0.07 1 11
    0.08 1 12
    0.09 1 14
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-07-25
  • 录用日期:  2018-10-17
  • 网络出版日期:  2019-04-20

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