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基于雷达测距和测速的GEO目标实时关联算法

宋丽萍 陈德峰 田甜 郭鑫

宋丽萍,陈德峰,田甜,等. 基于雷达测距和测速的GEO目标实时关联算法[J]. 北京航空航天大学学报,2023,49(8):2167-2175 doi: 10.13700/j.bh.1001-5965.2021.0615
引用本文: 宋丽萍,陈德峰,田甜,等. 基于雷达测距和测速的GEO目标实时关联算法[J]. 北京航空航天大学学报,2023,49(8):2167-2175 doi: 10.13700/j.bh.1001-5965.2021.0615
SONG L P,CHEN D F,TIAN T,et al. A real-time correlation algorithm for GEO targets based on radar ranging and velocity measurement[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(8):2167-2175 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0615
Citation: SONG L P,CHEN D F,TIAN T,et al. A real-time correlation algorithm for GEO targets based on radar ranging and velocity measurement[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(8):2167-2175 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0615

基于雷达测距和测速的GEO目标实时关联算法

doi: 10.13700/j.bh.1001-5965.2021.0615
基金项目: 国家自然科学基金(62071041);上海航天科技创新基金(SAST-2020078)
详细信息
    通讯作者:

    E-mail:cdf2008@bit.edu.cn

  • 中图分类号: V19;TN959.6

A real-time correlation algorithm for GEO targets based on radar ranging and velocity measurement

Funds: National Natural Science Foundation of China (62071041); Shanghai Aerospace and Technology Innovation Foundation (SAST-2020078)
More Information
  • 摘要:

    针对航迹密集情况下地球同步轨道(GEO)目标容易关联错误的问题,提出了一种基于雷达测距和测速二维判决的GEO目标实时关联算法。利用空间目标两行轨道根数(TLE)建立待关联初始库属目标集;根据空间目标轨道预报误差扩散规律设置粗关联门限,得到二次关联库属目标集;利用雷达测距和测速精度高的特点构建二次关联代价函数,根据归一化加权均方根误差最小原则得到关联结果。仿真结果表明:该算法在目标航迹密集的情况下取得了较好的关联效果,具有较高的关联正确率。

     

  • 图 1  坐标系及其的关系

    Figure 1.  Coordinate systems and their relationship

    图 2  实时关联算法流程

    Figure 2.  Flow chart of real-time association algorithm

    图 3  RSW坐标系下3个轴向误差

    Figure 3.  Three axial error curves in RSW coordinate system

    图 4  距离维航迹密集场景

    Figure 4.  Scenario of range dimension with dense tracks

    图 5  速度维航迹密集场景

    Figure 5.  Scenario of velocity dimension with dense tracks

    图 6  观测目标1粗关联效果

    Figure 6.  Rough-correlation effect of observation target No.1

    图 7  观测目标4粗关联效果

    Figure 7.  Rough-correlation effect of observation target No.4

    表  1  跟踪雷达参数信息

    Table  1.   Tracking-radar parameter information

    工作
    频段
    信号带宽/
    MHz
    天线波束
    宽度/(°)
    脉冲重复
    间隔/ms
    脉冲宽度/
    ms
    S50.155~201~4
    下载: 导出CSV

    表  2  测量信息中添加的高斯噪声(标准差)

    Table  2.   Gaussian noise (standard deviation) added to measurement information

    距离维/m方位维/mrad俯仰维/mrad速度维/(m·s−1)
    100.20.20.01
    下载: 导出CSV

    表  3  TLE目标集中目标更新周期分布

    Table  3.   Update period distribution of targets in TLE

    更新周期/d目标数量/个数量占比/%
    1157696.75
    2311.90
    350.31
    470.43
    其他100.61
      注:其他为更新周期大于等于5 d的目标个数。
    下载: 导出CSV

    表  4  观测目标1二次关联情况

    Table  4.   Secondary correlation of observation target No.1

    真实目标二次关联库属目标距离RMSE/km速度RMSE/(m·s−1)代价函
    数值
    关联
    结果
    3777632019202.3590.24936.48137776
    37207235.1420.40242.483
    37677131.7021.49024.832
    377760.8700.0020.158
    419034.5420.0820.881
    426628.6613.1264.118
    429510.6950.3460.409
    45807624.462258.579324.170
    461123.0990.3480.841
    下载: 导出CSV

    表  5  观测目标4二次关联情况

    Table  5.   Secondary correlation of observation target No.4

    真实目标二次关联库属目标距离RMSE/km速度RMSE/(m·s−1)代价函数值关联结果
    367442927218.43630.06610.083136744
    367440.00982.7727×10−40.0003
    4103484.49750.01010.0882
    4172954.09642.3420×10−40.0503
    434323.33550.01550.0185
    4382374.82451.024×10−40.0693
    452460.61030.12600.1265
    下载: 导出CSV

    表  6  目标关联实验结果

    Table  6.   Results of target correlation experiments

    序号样本总数/条关联成功概率/%
    基于协方差理论的关联算法基于距离辅助的关联算法 本文算法
    143290.5196.3399.54
    242588.9495.6999.04
    345390.2896.0799.13
    443590.3494.6399.02
    543789.7097.0299.08
    645891.7097.5499.11
    741989.5096.0699.12
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-10-19
  • 录用日期:  2022-01-02
  • 网络出版日期:  2022-01-11
  • 整期出版日期:  2023-08-31

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