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多模型GGIW-GLMB算法跟踪机动群目标

甘林海 刘进忙 王刚 李松

甘林海, 刘进忙, 王刚, 等 . 多模型GGIW-GLMB算法跟踪机动群目标[J]. 北京航空航天大学学报, 2018, 44(10): 2185-2192. doi: 10.13700/j.bh.1001-5965.2018.0053
引用本文: 甘林海, 刘进忙, 王刚, 等 . 多模型GGIW-GLMB算法跟踪机动群目标[J]. 北京航空航天大学学报, 2018, 44(10): 2185-2192. doi: 10.13700/j.bh.1001-5965.2018.0053
GAN Linhai, LIU Jinmang, WANG Gang, et al. Maneuvering group target tracking with multi-model GGIW-GLMB algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(10): 2185-2192. doi: 10.13700/j.bh.1001-5965.2018.0053(in Chinese)
Citation: GAN Linhai, LIU Jinmang, WANG Gang, et al. Maneuvering group target tracking with multi-model GGIW-GLMB algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(10): 2185-2192. doi: 10.13700/j.bh.1001-5965.2018.0053(in Chinese)

多模型GGIW-GLMB算法跟踪机动群目标

doi: 10.13700/j.bh.1001-5965.2018.0053
基金项目: 

国家自然科学基金 61703412

国家自然科学基金 61503407

详细信息
    作者简介:

    甘林海  男, 博士研究生。主要研究方向:群目标跟踪

    刘进忙  男, 教授, 博士生导师。主要研究方向:多源信息融合

    通讯作者:

    刘进忙, E-mail:liujinmang1@163.com

  • 中图分类号: TN953

Maneuvering group target tracking with multi-model GGIW-GLMB algorithm

Funds: 

National Natural Science Foundation of China 61703412

National Natural Science Foundation of China 61503407

More Information
  • 摘要:

    针对多个机动群目标跟踪问题,提出了一种多模型伽马高斯逆威夏特-广义标签多贝努利(MM-GGIW-GLMB)算法。采用多模型算法对群目标进行运动建模,利用最适高斯(BFG)近似在预测阶段对多模型进行融合,减小了多模型算法的运算量,为进一步提高算法在目标机动阶段的跟踪性能,引入强跟踪滤波器(STF)对BFG算法得到的预测状态协方差进行修正。利用最优次模式分配(OSPA)距离及其一倍标准差和航迹标签正确率衡量算法对机动群目标的跟踪性能。仿真结果表明,本文算法能够提升对机动群目标的跟踪精度和稳定性。

     

  • 图 1  运动轨迹仿真背景及质心位置一次仿真估计结果

    Figure 1.  Motion trajectory, background and estimated centroid position in one simulation

    图 2  质心状态、扩展状态及量测比率OSPA距离及其一倍标准差

    Figure 2.  OSPA distance of centroid state, extension state and measurement rate and their one standard deviation

    图 3  目标数目估计及其一倍标准差

    Figure 3.  Target number estimation and its one standard deviation

    图 4  MM-GGIW-GLMB及GGIW-GLMB算法各时刻真实航迹频次

    Figure 4.  Frequency of real track at each moment in MM-GGIW-GLMB and GGIW-GLMB algorithms

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出版历程
  • 收稿日期:  2018-01-22
  • 录用日期:  2018-04-20
  • 刊出日期:  2018-10-20

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