高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于JVC的紧凑型地波雷达海上目标点迹-航迹最优关联方法

戴永寿 马鹏 孙伟峰 刘培学 纪永刚 庞真真

戴永寿, 马鹏, 孙伟峰, 刘培学, 纪永刚, 庞真真. 基于JVC的紧凑型地波雷达海上目标点迹-航迹最优关联方法[J]. 电子与信息学报, 2021, 43(10): 2832-2839. doi: 10.11999/JEIT200604
引用本文: 戴永寿, 马鹏, 孙伟峰, 刘培学, 纪永刚, 庞真真. 基于JVC的紧凑型地波雷达海上目标点迹-航迹最优关联方法[J]. 电子与信息学报, 2021, 43(10): 2832-2839. doi: 10.11999/JEIT200604
Yongshou DAI, Peng MA, Weifeng SUN, Peixue LIU, Yonggang JI, Zhenzhen PANG. An Optimal Plot-to-Track Association Method Based on JVC Algorithm for Maritime Target with Compact HFSWR[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2832-2839. doi: 10.11999/JEIT200604
Citation: Yongshou DAI, Peng MA, Weifeng SUN, Peixue LIU, Yonggang JI, Zhenzhen PANG. An Optimal Plot-to-Track Association Method Based on JVC Algorithm for Maritime Target with Compact HFSWR[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2832-2839. doi: 10.11999/JEIT200604

基于JVC的紧凑型地波雷达海上目标点迹-航迹最优关联方法

doi: 10.11999/JEIT200604
基金项目: 国家重点研发计划项目(2017YFC1405202, 2017YFC1405203),国家自然科学基金(62071493, 61831010, 61501520),中央高校基本科研业务费项目(19CX02046A)
详细信息
    作者简介:

    戴永寿:男,1963年生,教授,研究方向为地震信号处理、海洋环境监测等

    马鹏:男,1993年生,硕士生,研究方向为紧凑型高频地波雷达目标探测与跟踪

    孙伟峰:男,1982年生,副教授,研究方向为紧凑型高频地波雷达目标探测与跟踪、图像处理等

    刘培学:男,1983年生,博士生,研究方向为紧凑型高频地波雷达目标探测与跟踪

    纪永刚:男,1977年生,研究员,研究方向为紧凑型高频地波雷达目标探测、海上目标多手段融合探测、新体制超视距雷达海态监测等

    庞真真:女,1996年生,硕士生,研究方向为紧凑型高频地波雷达目标探测与跟踪

    通讯作者:

    孙伟峰 sunwf@upc.edu.cn

  • 中图分类号: TN953

An Optimal Plot-to-Track Association Method Based on JVC Algorithm for Maritime Target with Compact HFSWR

Funds: The National Key R&D Program of China (2017YFC1405202, 2017YFC1405203), The National Natural Science Foundation of China (62071493, 61831010, 61501520), The Fundamental Research Funds for the Central Universities (19CX02046A)
  • 摘要: 紧凑型地波雷达由于接收天线阵列孔径减小导致对海上目标的定位精度低,在多目标跟踪算法中采用序贯式的点迹-航迹关联方式易发生误关联导致航迹断裂、误跟踪等问题。对此,该文将多目标点迹-航迹关联转化为最优分配问题,提出一种基于JVC算法的多目标点迹-航迹最优关联方法。对于关联波门重叠区域内存在公共候选点迹的多条航迹,首先以雷达获取的目标多普勒速度、距离与方位角作为目标特征参数,利用最小代价函数确定公共候选点迹与所有航迹之间的相似度,得到关联代价矩阵;然后以总关联代价最小化作为优化准则,采用JVC算法求解得到最优的点迹-航迹关联结果。利用仿真与实测目标数据开展了点迹-航迹关联实验,并与序贯最近邻关联方法的关联结果进行了对比。实验结果表明:采用该文所提方法跟踪得到的航迹时长明显优于序贯最近邻关联方法的结果,解决了序贯式关联因关联错误导致的航迹断裂、误跟踪等问题,提高了航迹跟踪的连续性。
  • 图  1  关联波门示意图

    图  2  紧凑型HFSWR目标仿真示例

    图  3  基于仿真数据的跟踪结果对比

    图  4  目标参数误差分析

    图  5  采用实测数据跟踪时不同时长的航迹数目对比

    图  6  采用实测数据的跟踪结果对比

    表  1  仿真目标的参数

    初始距离(km)初始方位角(°)初始多普勒速$({\rm{km/h}})$帧数
    目标1 147.2 8.4 20.8 180
    目标2 151.6 8.7 19.7 180
    目标3 157.4 11.1 19.4 180
    目标4 138.1 –19.5 30.6 180
    目标5 138.8 –19.0 19.1 180
    下载: 导出CSV

    表  2  不同跟踪时长的航迹数量对比

    方法跟踪时长>30 min跟踪时长>40 min跟踪时长>50 min
    航迹总数平均跟踪时长(min)航迹总数平均跟踪时长(min)航迹总数平均跟踪时长(min)
    序贯最近邻关联方法18146.912352.49254.8
    本文方法14569.110980.78193.7
    下载: 导出CSV

    表  3  目标个例详细信息

    船名MMSI船长(m)船宽(m)吃水深度(m)初始距离${\rm{(km)}}$初始方位角${(^ \circ })$多普勒速度$({\rm{km/h}})$跟踪时长(m)
    JIN YUAN XING 16 413271210 224 32 12.4 91.7 10.4 20.1 124
    TONG DA 698 412454070 103 16 3.5 26.6 28.8 –10.2 180
    YONG XING ZHOU 413203000 228 32 11.4 27.1 26.4 –12.2 150
    下载: 导出CSV

    表  4  采用两种方法时的跟踪结果比较

    关联方法正确关联航迹数目关联正确率(%)平均运行时间(s)
    NNDA2953.749.61
    本文方法4481.554.7
    下载: 导出CSV
  • [1] 纪永刚, 张杰, 王祎鸣, 等. 紧凑型高频地波雷达目标探测研究进展[J]. 中国海洋大学学报, 2017, 47(2): 1–7. doi: 10.16441/j.cnki.hdxb.20160285

    JI Yonggang, ZHANG Jie, WANG Yiming, et al. An overview of target monitoring with compact HFSWR[J]. Periodical of Ocean University of China, 2017, 47(2): 1–7. doi: 10.16441/j.cnki.hdxb.20160285
    [2] 叶磊, 王勇, 杨强, 等. 基于对数行列式散度与对称对数行列式散度的高频地波雷达目标检测器[J]. 电子与信息学报, 2019, 41(8): 1931–1938. doi: 10.11999/JEIT181078

    YE Lei, WANG Yong, YANG Qiang, et al. High frequency surface wave radar detector based on log-determinant divergence and symmetrized log-determinant divergence[J]. Journal of Electronics &Information Technology, 2019, 41(8): 1931–1938. doi: 10.11999/JEIT181078
    [3] PARK S, CHO C J, KU B, et al. Compact HF surface wave radar data generating simulator for ship detection and tracking[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(6): 969–973. doi: 10.1109/LGRS.2017.2691741
    [4] SMITH M, ROARTY H, GLENN S, et al. Methods of associating CODAR seasonde vessel detection data into unique tracks[C]. 2013 IEEE OCEANS, San Diego, USA, 2013: 1–5. doi: 10.23919/OCEANS.2013.6741197.
    [5] LU Bo, WEN Biyang, TIAN Yingwei, et al. A vessel detection method using compact-array HF radar[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(11): 2017–2021. doi: 10.1109/LGRS.2017.2748142
    [6] HELZEL T, HANSEN B, KNIEPHOFF M, et al. Introduction of the compact HF radar WERA-S[C]. 2012 IEEE/OES Baltic International Symposium (BALTIC), Klaipeda, Lithuania, 2012: 1–3. doi: 10.1109/BALTIC.2012.6249215.
    [7] JI Yonggang, ZHANG Jie, WANG Yiming, et al. Target monitoring using small-aperture compact high-frequency surface wave radar[J]. IEEE Aerospace and Electronic Systems Magazine, 2018, 33(3): 22–31. doi: 10.1109/MAES.2018.170023
    [8] SUN Weifeng, HUANG Weimin, JI Yonggang, et al. A vessel azimuth and course joint re-estimation method for compact HFSWR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(2): 1041–1051. doi: 10.1109/TGRS.2019.2943065
    [9] SUN Weifeng, HUANG Weimin, JI Yonggang, et al. Vessel tracking with small-aperture compact high-frequency surface wave radar[C]. OCEANS 2019- Marseille, Marseille, France, 2019: 1–4. doi: 10.1109/OCEANSE.2019.8867267.
    [10] 辛云宏, 杨万海. 被动多站多目标的测量数据关联算法研究[J]. 宇航学报, 2005, 26(6): 748–752, 797. doi: 10.3321/j.issn:1000-1328.2005.06.015

    XIN Yunhong and YANG Wanhai. A method of the passive multi-sensor multi-target measurement data association[J]. Journal of Astronautics, 2005, 26(6): 748–752, 797. doi: 10.3321/j.issn:1000-1328.2005.06.015
    [11] CHEN Qinxin, YAN Yude, and DAI Yuewei. Joint nearest neighbor data association based on interacting multiple model Kalman filtering[C]. 2016 IEEE International Conference on Computer and Communications (ICCC), Chengdu, China, 2016: 75–79. doi: 10.1109/CompComm.2016.7924668.
    [12] 李保珠, 关键, 董云龙. 基于航迹矢量检测的雷达与电子支援设施抗差关联算法[J]. 电子与信息学报, 2019, 41(1): 123–129. doi: 10.11999/JEIT180303

    LI Baozhu, GUAN Jian, and DONG Yunlong. Anti-bias track association algorithm of radar and electronic support measurements based on track vectors detection[J]. Journal of Electronics &Information Technology, 2019, 41(1): 123–129. doi: 10.11999/JEIT180303
    [13] HUANG Yuan, SONG T L, and KIM D S. Linear multitarget integrated probabilistic data association for multiple detection target tracking[J]. IET Radar, Sonar & Navigation, 2018, 12(9): 945–953. doi: 10.1049/iet-rsn.2017.0481
    [14] ZHANG Hui, LIU Yongxin, JI Yonggang, et al. Vessel fusion tracking with a dual-frequency high-frequency surface wave radar and calibrated by an automatic identification system[J]. Acta Oceanologica Sinica, 2018, 37(7): 131–140. doi: 10.1007/s13131-018-1250-0
    [15] 李文超, 邹焕新, 雷琳, 等. 目标数据关联技术综述[J]. 计算机仿真, 2014, 31(3): 1–5, 10. doi: 10.3969/j.issn.1006-9348.2014.03.001

    LI Wenchao, ZOU Huanxin, LEI Lin, et al. A survey of target data association[J]. Computer Simulation, 2014, 31(3): 1–5, 10. doi: 10.3969/j.issn.1006-9348.2014.03.001
    [16] 康旭超, 何广军, 陈峰, 等. 密集杂波下的模糊数据关联多目标跟踪算法[J]. 探测与控制学报, 2019, 41(4): 56–61, 65.

    KANG Xuchao, HE Guangjun, CHEN Feng, et al. Fuzzy data associated with multi-target tracking algorithm under dense clutter[J]. Journal of Detection &Control, 2019, 41(4): 56–61, 65.
    [17] WINTER M, SCHMIDLIN V, and FAVIER G. Classical and neural solutions for plot-to-track association[C]. SPIE 3163, Signal and Data Processing of Small Targets, San Diego, USA, 1997: 546–557. doi: 10.1117/12.279537.
    [18] BORDONARO S, WILLETT P, and BAR-SHALOM Y. Decorrelated unbiased converted measurement Kalman filter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2): 1431–1444. doi: 10.1109/TAES.2014.120563
    [19] 盛卫东, 林两魁, 安玮, 等. 基于全局最优的被动多传感器多目标轨迹关联算法[J]. 电子与信息学报, 2010, 32(7): 1621–1625. doi: 10.3724/SP.J.1146.2009.01091

    SHENG Weidong, LIN Liangkui, AN Wei, et al. A passive multisensor multitarget track association algorithm based on global optimization[J]. Journal of Electronics &Information Technology, 2010, 32(7): 1621–1625. doi: 10.3724/SP.J.1146.2009.01091
    [20] NIKOLIC D, STOJKOVIC N, and LEKIC N. Maritime over the horizon sensor integration: High frequency surface-wave- radar and automatic identification system data integration algorithm[J]. Sensors, 2018, 18(4): 1147. doi: 10.3390/s18041147
  • 加载中
图(6) / 表(4)
计量
  • 文章访问数:  1280
  • HTML全文浏览量:  602
  • PDF下载量:  113
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-07-21
  • 修回日期:  2020-12-16
  • 网络出版日期:  2021-01-05
  • 刊出日期:  2021-10-18

目录

    /

    返回文章
    返回