回波幅度信息辅助的群目标航迹起始方法

靳标 李聪 张贞凯

靳标, 李聪, 张贞凯. 回波幅度信息辅助的群目标航迹起始方法[J]. 雷达学报, 2020, 9(4): 723–729. doi: 10.12000/JR19088
引用本文: 靳标, 李聪, 张贞凯. 回波幅度信息辅助的群目标航迹起始方法[J]. 雷达学报, 2020, 9(4): 723–729. doi: 10.12000/JR19088
JIN Biao, LI Cong, and ZHANG Zhenkai. Group target track initiation method aided by echo amplitude information[J]. Journal of Radars, 2020, 9(4): 723–729. doi: 10.12000/JR19088
Citation: JIN Biao, LI Cong, and ZHANG Zhenkai. Group target track initiation method aided by echo amplitude information[J]. Journal of Radars, 2020, 9(4): 723–729. doi: 10.12000/JR19088

回波幅度信息辅助的群目标航迹起始方法

DOI: 10.12000/JR19088
基金项目: 国家自然科学基金(61701416, 61871203),中国博士后科学基金(2017M613214)
详细信息
    作者简介:

    靳 标(1986–),男,山西翼城人,博士,江苏科技大学电信学院副教授,研究方向为雷达信号检测与目标跟踪,认知雷达发射波形设计等。E-mail: biaojin@just.edu.cn

    李 聪(1994–),男,河北唐山人。现为西安交通大学电子与信息学部硕士研究生。主要研究方向为阵列信号处理,智能天线系统。E-mail: a1870692245@163.com

    张贞凯(1982–),男,江苏徐州人,博士,副教授,2013年在南京航空航天大学电子信息工程学院获得博士学位,现担任江苏科技大学电子信息学院副教授,主要研究方向为雷达通信一体化技术、雷达信号处理、水下目标定位等研究,目前已发表论文78篇。E-mail: zhangzhenkai@just.edu.cn

    通讯作者:

    靳标 biaojin@just.edu.cn

  • 责任主编:王海鹏 Corresponding Editor: WANG Haipeng
  • 中图分类号: TN957.52

Group Target Track Initiation Method Aided by Echo Amplitude Information

Funds: The National Natural Science Foundation of China (61701416, 61871203), The Project funded by China Postdoctoral Science Foundation (2017M613214)
More Information
  • 摘要: 航迹起始是群目标跟踪的首要环节,其性能好坏直接影响着目标跟踪航迹的质量。传统的群目标航迹起始方法仅利用目标的位置信息完成分群检测和等效量测求解等步骤,没有充分利用回波幅度信息,存在分群检测不理想、等效量测求解不准确等问题,有可能引起失跟现象。针对此问题,该文提出一种回波幅度信息辅助的群目标航迹起始方法。首先利用目标位置信息和幅度信息完成分群检测,然后综合采用幅度加权和位置加权求解等效量测,最后基于修正的逻辑法进行群目标航迹起始。该文方法在分群检测和求解等效量测等步骤充分利用了回波幅度信息,不仅可以在集群数量未知的情况下正确划分群,而且降低了失跟率,提高了群目标的跟踪性能。仿真结果验证了所提方法的有效性。

     

  • 图  1  昆虫种群空间密度分布场景

    Figure  1.  Spatial density distribution of insect population

    图  2  本文算法的流程

    Figure  2.  The flow of the algorithm in this paper

    图  3  分群检测的具体流程

    Figure  3.  The specific process of cluster detection

    图  4  量测点迹空间分布

    Figure  4.  The spatial distribution of measuring point trace

    图  5  基于位置信息的分群结果

    Figure  5.  The clustering result based on location information

    图  6  幅度信息辅助的分群结果

    Figure  6.  The clustering result aided by echo amplitude information

    图  7  等效量测对比

    Figure  7.  Equivalent measurement comparison

    图  8  不同权值大小时的起始航迹对比

    Figure  8.  Comparison of initial tracks with different weights

    表  1  幅度、距离不同权值下航迹起始成功率

    Table  1.   The success rate of track start under different weights of amplitude and distance

    $\alpha = 0.8, \beta = 0.2$$\alpha = 0.5, \beta = 0.5$$\alpha = 0.2, \beta = 0.8$$\alpha = 0.1, \beta = 0.9$$\alpha = 0, {\rm{}}\beta = 1.0$
    航迹起始成功率(%)8093989589
    下载: 导出CSV
  • [1] NIEDFELDT P C and BEARD R W. Convergence and complexity analysis of recursive-RANSAC: A new multiple target tracking algorithm[J]. IEEE Transactions on Automatic Control, 2016, 61(2): 456–461.
    [2] ÚBEDA-MEDINA L, GARCÍA-FERNÁNDEZ Á F, and GRAJAL J. Adaptive auxiliary particle filter for track-before-detect with multiple targets[J]. IEEE Transactions on Aerospace and Electronic Systems, 2017, 53(5): 2317–2330. doi: 10.1109/TAES.2017.2691958
    [3] ZHU Yun, WANG Jun, and LIANG Shuang. Efficient joint probabilistic data association filter based on Kullback-Leibler divergence for multi-target tracking[J]. IET Radar, Sonar & Navigation, 2017, 11(10): 1540–1548.
    [4] VIVONE G and BRACA P. Joint probabilistic data association tracker for extended target tracking applied to X-band marine radar data[J]. IEEE Journal of Oceanic Engineering, 2016, 41(4): 1007–1019. doi: 10.1109/JOE.2015.2503499
    [5] LIAN Feng, HAN Chongzhao, LIU Weifeng, et al. Unified cardinalized probability hypothesis density filters for extended targets and unresolved targets[J]. Signal Processing, 2012, 92(7): 1729–1744. doi: 10.1016/j.sigpro.2012.01.009
    [6] CAO Xianbin, JIANG Xiaolong, LI Xiaomei, et al. Correlation-based tracking of multiple targets with hierarchical layered structure[J]. IEEE Transactions on Cybernetics, 2018, 48(1): 90–102. doi: 10.1109/TCYB.2016.2625320
    [7] 王聪, 王海鹏, 何友, 等. 基于ICP的稳态部分可辨编队目标精细跟踪算法[J]. 北京航空航天大学学报, 2017, 43(6): 1123–1131.

    WANG Cong, WANG Haipeng, HE You, et al. Refined tracking algorithm for steady partly resolvable group targets based on ICP[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(6): 1123–1131.
    [8] 方琳琳, 周超, 王锐, 等. 昆虫目标雷达散射截面积特征辅助跟踪算法[J]. 雷达学报, 2019, 8(5): 598–605. doi: 10.12000/JR19067

    FANG Linlin, ZHOU Chao, WANG Rui, et al. RCS feature-aided insect target tracking algorithm[J]. Journal of Radars, 2019, 8(5): 598–605. doi: 10.12000/JR19067
    [9] 封洪强. 雷达在昆虫学研究中的应用[J]. 植物保护, 2011, 37(5): 1–13. doi: 10.3969/j.issn.0529-1542.2011.05.001

    FENG Hongqiang. Applications of radar in entomological research[J]. Plant Protection, 2011, 37(5): 1–13. doi: 10.3969/j.issn.0529-1542.2011.05.001
    [10] 耿文东. 基于群目标几何中心的群起始算法研究[J]. 系统工程与电子技术, 2008, 30(2): 269–272. doi: 10.3321/j.issn:1001-506X.2008.02.019

    GENG Wendong. Study of group-initialization method based on group-target center of geometry[J]. Systems Engineering and Electronics, 2008, 30(2): 269–272. doi: 10.3321/j.issn:1001-506X.2008.02.019
    [11] 周大庆, 耿文东, 倪春雷. 基于编队目标重心的航迹起始方法研究[J]. 无线电工程, 2010, 40(2): 32–34. doi: 10.3969/j.issn.1003-3106.2010.02.011

    ZHOU Daqing, GENG Wendong, and NI Chunlei. Study of track initiation method based on barycenter of formation target[J]. Radio Engineering of China, 2010, 40(2): 32–34. doi: 10.3969/j.issn.1003-3106.2010.02.011
    [12] KOCH J W. Bayesian approach to extended object and cluster tracking using random matrices[J]. IEEE Transactions on Aerospace and Electronic Systems, 2008, 44(3): 1042–1059. doi: 10.1109/TAES.2008.4655362
    [13] 韩玉兰, 朱洪艳, 韩崇昭. 采用随机矩阵的多扩展目标滤波器[J]. 西安交通大学学报, 2015, 49(7): 98–104. doi: 10.7652/xjtuxb201507017

    HAN Yulan, ZHU Hongyan, and HAN Chongzhao. A multi-target filter based on random matrix[J]. Journal of Xian Jiaotong University, 2015, 49(7): 98–104. doi: 10.7652/xjtuxb201507017
    [14] JIN Biao, JIU Bo, SU Tao, et al. Switched Kalman filter-interacting multiple model algorithm based on optimal autoregressive model for manoeuvring target tracking[J]. IET Radar, Sonar & Navigation, 2015, 9(2): 199–209.
    [15] GNING A, MIHAYLOVA L, MASKELL S, et al. Ground target group structure and state estimation with particle filtering[C]. The 2008 11th International Conference on Information Fusion, Cologne, Germany, 2008: 1–8.
    [16] LI Yunxiang, XIAO Huaitie, SONG Zhiyong, et al. A new multiple extended target tracking algorithm using PHD filter[J]. Signal Processing, 2013, 93(12): 3578–3588. doi: 10.1016/j.sigpro.2013.05.011
    [17] LAN Jian and LI X R. Extended-object or group-target tracking using random matrix with nonlinear measurements[J]. IEEE Transactions on Signal Processing, 2019, 67(19): 5130–5142. doi: 10.1109/TSP.2019.2935866
    [18] MIHAYLOVA L, CARMI A Y, SEPTIER F, et al. Overview of Bayesian sequential Monte Carlo methods for group and extended object tracking[J]. Digital Signal Processing, 2014, 25: 1–16. doi: 10.1016/j.dsp.2013.11.006
    [19] DANIYAN A, LAMBOTHARAN S, DELIGIANNIS A, et al. Bayesian multiple extended target tracking using labeled random finite sets and splines[J]. IEEE Transactions on Signal Processing, 2018, 66(22): 6076–6091. doi: 10.1109/TSP.2018.2873537
    [20] 何友, 修建娟, 关欣. 雷达数据处理及应用[M]. 3版. 北京: 电子工业出版社, 2013: 108–174.

    HE You, XIU Jianjuan, and GUAN Xin. Radar Data Processing with Applications[M]. 3rd ed. Beijing: Publishing House of Electronics Industry, 2013: 108–174.
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出版历程
  • 收稿日期:  2019-09-27
  • 修回日期:  2019-12-17
  • 网络出版日期:  2020-08-28

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