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

PHD粒子滤波中目标状态提取方法研究

唐续 魏平 陈欣

唐续, 魏平, 陈欣. PHD粒子滤波中目标状态提取方法研究[J]. 电子与信息学报, 2010, 32(11): 2691-2694. doi: 10.3724/SP.J.1146.2009.01580
引用本文: 唐续, 魏平, 陈欣. PHD粒子滤波中目标状态提取方法研究[J]. 电子与信息学报, 2010, 32(11): 2691-2694. doi: 10.3724/SP.J.1146.2009.01580
Tang Xu, Wei Ping, Chen Xin. Extracting Targets State from Particle Approximation of the PHD[J]. Journal of Electronics and Information Technology, 2010, 32(11): 2691-2694. doi: 10.3724/SP.J.1146.2009.01580
Citation: Tang Xu, Wei Ping, Chen Xin. Extracting Targets State from Particle Approximation of the PHD[J]. Journal of Electronics and Information Technology, 2010, 32(11): 2691-2694. doi: 10.3724/SP.J.1146.2009.01580

PHD粒子滤波中目标状态提取方法研究

doi: 10.3724/SP.J.1146.2009.01580

Extracting Targets State from Particle Approximation of the PHD

  • 摘要: 采用概率假设密度(PHD)粒子滤波进行多目标跟踪时,各时刻的目标状态表现为大量的加权粒子,需以一定方法从该粒子近似中提取出来。该文提出一种增强的目标状态提取方法,先以k-means算法对粒子进行空间分布的聚类,再于各类中寻找粒子权的峰值位置作为目标状态的估计。仿真结果表明:由于综合利用了粒子的权值和空间分布信息,该算法具有比现有算法更小的目标状态估计误差。
  • Mahler R. Statistical Multisource-Multitarget Information Fusion[M]. Artech House, Boston, 2007: 711-715.[2]Ba-ngu vo, Singh S, and Doucet A. Sequential monte carlo methods for multi-target filtering with random finite sets[J].IEEE Transactions on Aerospace and Electronic Systems.2005, 41(4):1224-1245[3]Tobias M and Lanterman A D. Probability hypothesis density-based multitarget tracking with bistatic range and doppler observations[J].IET, Radar, Sonar and Navigation.2005, 152(3):195-205[4]Jain A K, Murty M N, and Flynn P J. Data clustering: a review[J].ACM Computing Surveys.1999, 31(3):264-323[5]Ba-ngu vo and Wing-kin MA. The gaussian mixture probability hypothesis density filter[J].IEEE Transactions on Signal Processing.2006, 54(11):4091-4104[6]Tobias M and Lanterman A D. Techniques for birth-particle placement in the probability hypothesis density particle filter applied to passive radar[J].IET, Radar, Sonar and Navigation.2008, 2(5):351-365[7]Hoffman J and Mahler R. Multitarget miss distance via optimal assignment[J].IEEE Transactions on Systems, Man and Cybernetics-Part A.2004, 34(3):327-336[8]Mahler R. PHD filters of higher order in target number[J]. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(4): 1523-1543.[9]Clark D, Ristic B, and Ba-ngu Vo. PHD Filtering with target amplitude feature[C]. 11th International Conference on Information Fusion. Cologne, Germany, Jun. 30-July 3, 2008: 1-7.[10]Streit R L. PHD intensity filtering is one step of a MAP estimation algorithm for positron emission tomography[C]. Proc of the International Conference on Information Fusion, Seattle, WA, July 6-9, 2009: 308-315.
  • 加载中
计量
  • 文章访问数:  3191
  • HTML全文浏览量:  76
  • PDF下载量:  1834
  • 被引次数: 0
出版历程
  • 收稿日期:  2009-12-11
  • 修回日期:  2010-05-04
  • 刊出日期:  2010-11-19

目录

    /

    返回文章
    返回

    官方微信,欢迎关注