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

基于均方根容积粒子的SMC-PHD算法

刘哲 王祖林 徐迈 刘景贤 杨蓝

刘哲, 王祖林, 徐迈, 等 . 基于均方根容积粒子的SMC-PHD算法[J]. 北京航空航天大学学报, 2015, 41(10): 1950-1958. doi: 10.13700/j.bh.1001-5965.2015.0100
引用本文: 刘哲, 王祖林, 徐迈, 等 . 基于均方根容积粒子的SMC-PHD算法[J]. 北京航空航天大学学报, 2015, 41(10): 1950-1958. doi: 10.13700/j.bh.1001-5965.2015.0100
LIU Zhe, WANG Zulin, XU Mai, et al. SMC-PHD algorithm based on squared cubature particles[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(10): 1950-1958. doi: 10.13700/j.bh.1001-5965.2015.0100(in Chinese)
Citation: LIU Zhe, WANG Zulin, XU Mai, et al. SMC-PHD algorithm based on squared cubature particles[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(10): 1950-1958. doi: 10.13700/j.bh.1001-5965.2015.0100(in Chinese)

基于均方根容积粒子的SMC-PHD算法

doi: 10.13700/j.bh.1001-5965.2015.0100
详细信息
    作者简介:

    刘哲(1981-),男,山西运城人,博士研究生,liuzhe201@buaa.edu.cn

    通讯作者:

    王祖林(1965-),男,湖北潜江人,教授,wzulin@buaa.edu.cn,主要研究方向为雷达与电子对抗.

  • 中图分类号: TP242

SMC-PHD algorithm based on squared cubature particles

  • 摘要: 传统的序贯蒙特卡罗概率假设密度(SMC-PHD)算法采用状态转移密度作为重要性采样函数.当目标非线性运动时,少数粒子将具有较大的权值,导致估计精度低、结果发散.针对上述问题,提出了一种基于均方根容积卡尔曼滤波(SCKF)和统计门限技术的重要性采样函数设计方法.在重要性采样函数估计时,首先利用SCKF对重要性采样函数的均值和协方差阵进行预测,而后利用统计门限技术提取与重要性采样粒子相关联的量测.通过相应的权值对所提取的量测进行合并,更新重要性采样函数的均值和协方差阵.在此基础上将设计的重要性采样函数应用于SMC-PHD的强度预测和更新,最终实现多目标状态和数目的估计.实验表明,本算法在非线性多目标跟踪中具有精度高、估计结果稳定的优点.

     

  • [1] Bocquel M,Driessen H,Bagchi A.Multitarget tracking with interacting population-based MCMC-PF[C]∥IEEE 15th International Conference on Information Fusion(FUSION).Piscataway,NJ:IEEE Press,2012:74-81.
    [2] Ristic B.Particle filters for random set models[M].New York:Springer,2013.
    [3] Mallick M,Vo B N,Kirubarajan T,et al.Introduction to the issue on multitarget tracking[J].IEEE Journal of Selected Topics in Signal Processing,2013,7(3):373-375.
    [4] Vermaak J,Godsill S J,Perez P.Monte carlo filtering for multi target tracking and data association[J].IEEE Transactions on Aerospace and Electronic Systems,2005,41(1):309-332.
    [5] Wu J,Hu S,Wang Y.Adaptive multifeature visual tracking in a probability-hypothesis-density filtering framework[J].Signal Processing,2013,93(11):2915-2926.
    [6] Uney M,Clark D E,Julier S J.Distributed fusion of PHD filters via exponential mixture densities[J].IEEE Journal of Selected Topics in Signal Processing,2013,7(3):521-531.
    [7] Mahler R P S.Multitarget Bayes filtering via first-order multitarget moments[J].IEEE Transactions on Aerospace and Electronic Systems,2003,39(4):1152-1178.
    [8] 杨峰,王永齐,梁彦,等.基于概率假设密度滤波方法的多目标跟踪技术综述[J].自动化学报,2013,39(11):1944-1956.Yang F,Wang Y Q,Liang Y,et al.A survey of PHD filter based multi-target tracking[J].Acta Automatica Sinica,2013,39(11):1944-1956(in Chinese).
    [9] Vo B N,Singh S,Doucet A.Sequential Monte Carlo methods for multitarget filtering with random finite sets[J].IEEE Transactions on Aerospace and Electronic Systems,2005,41(4):1224-1245.
    [10] Mahler R P S.Statistical multisource-multitarget information fusion[M].Norwood:Artech House,Inc.,2007.
    [11] Ristic B,Clark D,Vo B N.Improved SMC implementation of the PHD filter[C]∥13th Conference on Information Fusion(FUSION).Piscataway,NJ:IEEE Press,2010:1-8.
    [12] Ristic B,Clark D,Vo B N,et al.Adaptive target birth intensity for PHD and CPHD filters[J].IEEE Transactions on Aerospace and Electronic Systems,2012,48(2):1656-1668.
    [13] Punithakumar K,Kirubarajan T,Sinha A.Multiple-model probability hypothesis density filter for tracking maneuvering targets[J].IEEE Transactions on Aerospace and Electronic Systems,2008,44(1):87-98.
    [14] Baser E,Efe M.A novel auxiliary particle PHD filter[C]∥IEEE 15th International Conference on Information Fusion(FUSION).Piscataway,NJ:IEEE Press,2012:165-172.
    [15] Yoon J H,Kim D Y,Yoon K J.Efficient importance sampling function design for sequential Monte Carlo PHD filter[J].Signal Processing,2012,92(9):2315-2321.
    [16] Li T,Sun S,Sattar T P.High-speed sigma-gating SMC-PHD filter[J].Signal Processing,2013,93(9):2586-2593.
    [17] Arasaratnam I,Haykin S.Cubature Kalman filters[J].IEEE Transactions on Automatic Control,2009,54(6):1254-1269.
    [18] Schuhmacher D,Vo B T,Vo B N.A consistent metric for performance evaluation of multi-object filters[J].IEEE Transactions on Signal Processing,2008,56(8):3447-3457.
    [19] 汤琦,黄建国,杨旭东.航迹起始算法及性能仿真[J].系统仿真学报,2007,19(1):149-152.Tang Q,Huang J G,Yang X D.Algorithm of track initiation and performance evaluation[J].Journal of System Simulation,2007,19(1):149-152(in Chinese).
  • 加载中
计量
  • 文章访问数:  1024
  • HTML全文浏览量:  70
  • PDF下载量:  483
  • 被引次数: 0
出版历程
  • 收稿日期:  2015-02-17
  • 修回日期:  2015-04-30
  • 网络出版日期:  2015-10-20

目录

    /

    返回文章
    返回
    常见问答