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基于改进盖尔-沙普利算法的自动识别系统与双频地波雷达断裂航迹关联

张晖 曾显普 高亮

张晖, 曾显普, 高亮. 基于改进盖尔-沙普利算法的自动识别系统与双频地波雷达断裂航迹关联[J]. 电子与信息学报. doi: 10.11999/JEIT220005
引用本文: 张晖, 曾显普, 高亮. 基于改进盖尔-沙普利算法的自动识别系统与双频地波雷达断裂航迹关联[J]. 电子与信息学报. doi: 10.11999/JEIT220005
ZHANG Hui, ZENG Xianpu, GAO Liang. Track Segment Association of Automatic Identification System and Dual-frequency High-Frequency Surface Wave Radar Based on Improved Gale-Shapley Algorithm[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT220005
Citation: ZHANG Hui, ZENG Xianpu, GAO Liang. Track Segment Association of Automatic Identification System and Dual-frequency High-Frequency Surface Wave Radar Based on Improved Gale-Shapley Algorithm[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT220005

基于改进盖尔-沙普利算法的自动识别系统与双频地波雷达断裂航迹关联

doi: 10.11999/JEIT220005
基金项目: 国家重点研发计划(2017YFC1405200),国家自然科学基金(61701263)
详细信息
    作者简介:

    张晖:男,副教授,研究方向为智能信息处理、多传感数据融合等

    曾显普:男,硕士生,研究方向为高频地波雷达多目标跟踪与航迹关联

    高亮:男,硕士生,研究方向为高频地波雷达信号处理与仿真

    通讯作者:

    张晖 Hui.zhang@imu.edu.cn

  • 中图分类号: TN958

Track Segment Association of Automatic Identification System and Dual-frequency High-Frequency Surface Wave Radar Based on Improved Gale-Shapley Algorithm

Funds: The National Key Research and Development Program of China (2017YFC1405200), The National Natural Science Foundation of China (61701263)
  • 摘要: 高频地波雷达(HFSWR)可以实现大范围海上船只目标的连续探测,但是海杂波等干扰因素的影响容易造成跟踪航迹的断裂。目前关于地波雷达航迹关联的研究中,通常忽略了航迹断裂的情况,将航迹关联视为二分图匹配问题,这会导致可能将单一目标的断裂航迹判断为多个目标,从而引起目标的误关联。针对上述情况,该文结合模糊综合评判和迭代搜索算法,首次将盖尔-沙普利算法引入航迹关联领域,并且对其进行改进以满足航迹断裂时的多对多航迹关联情况。在该算法中,通过计算航迹之间的模糊综合评判值来得到航迹之间的倾向度序列,再由迭代搜索对航迹进行聚类以获得航迹集群,最后将航迹集群及倾向度序列输入盖尔-沙普利算法来进行数轮博弈以给出关联结果。利用双频率高频地波雷达和船只自动识别系统(AIS)的仿真数据与实测数据进行实验测试,实验结果表明:所提出的算法解决了在航迹断裂情况下的多传感器航迹关联问题,且在密集区域的航迹关联效果优于传统算法。
  • 图  1  航迹断裂时的关联情况示意图

    图  2  时间冲突时的决策流程图

    图  3  AIS和HFSWR仿真数据航迹关联结果

    图  4  AIS和HFSWR实测数据航迹关联结果

    图  5  AIS和HFSWR仿真数据局部航迹关联结果

    图  6  AIS和HFSWR双频航迹关联结果

    图  7  非合作目标航迹关联结果

    表  1  航迹集G1详细情况

    航迹标号倾向度表(正序)航迹所属时间
    A1B1, B3, B203~19
    A2B3, B1, B230~43
    A3B3, B2, B123~46
    A4B1, B2, B321~49
    B1A2, A3, A4, A106~30
    B2A3, A4, A1, A212~36
    B3A3, A4, A2, A115~51
    下载: 导出CSV

    表  2  航迹集G1匹配过程

    邀约轮数该轮邀约结束时的匹配结果
    第1轮A1-B1; A2-无 A3-B3; A4-B1
    第2轮A1-无; A2-B1; A3-B3; A4-无
    第3轮A1-B2; A2-B1; A3-B3; A4-B2
    下载: 导出CSV

    表  3  航迹关联结果性能分析

    实验数据和所用算法关联比例(%)关联正确率(%)距离RMSE(km)方位RMSE(°)速度RMSE(km/h)计算耗时(s)
    仿真数据GNNDA48.2088.810.40770.27590.44015.73
    仿真数据IGS75.1897.130.38630.24060.382611.82
    实测数据GNNDA42.06未知1.99301.89350.50246.49
    实测数据IGS60.75未知1.87831.67100.343813.05
    下载: 导出CSV

    表  4  实测数据非合作目标双频航迹关联个例分析(km/h)

    航迹名航迹时间k1点速度k2点速度k3点速度k4点速度k5点速度k6点速度
    F1T109:57~10:22–13.48–12.26–12.86–13.33无数值无数值
    F1T210:31~10:46无数值无数值无数值无数值–13.23–13.02
    F2T109:57~10:12–13.31–12.48无数值无数值无数值无数值
    F2T210:18~10:46无数值无数值–12.43–13.05–13.01–12.78
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-01-05
  • 修回日期:  2022-08-31
  • 网络出版日期:  2022-09-02

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