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一种新的避免航迹合并的联合综合概率数据关联滤波器

朱昀 王俊 陈刚 郭帅

朱昀, 王俊, 陈刚, 郭帅. 一种新的避免航迹合并的联合综合概率数据关联滤波器[J]. 电子与信息学报, 2017, 39(10): 2346-2353. doi: 10.11999/JEIT170085
引用本文: 朱昀, 王俊, 陈刚, 郭帅. 一种新的避免航迹合并的联合综合概率数据关联滤波器[J]. 电子与信息学报, 2017, 39(10): 2346-2353. doi: 10.11999/JEIT170085
ZHU Yun, WANG Jun, CHEN Gang, GUO Shuai. Novel Track Coalescence Avoiding Joint Integrated Probabilistic Data Association Filter[J]. Journal of Electronics & Information Technology, 2017, 39(10): 2346-2353. doi: 10.11999/JEIT170085
Citation: ZHU Yun, WANG Jun, CHEN Gang, GUO Shuai. Novel Track Coalescence Avoiding Joint Integrated Probabilistic Data Association Filter[J]. Journal of Electronics & Information Technology, 2017, 39(10): 2346-2353. doi: 10.11999/JEIT170085

一种新的避免航迹合并的联合综合概率数据关联滤波器

doi: 10.11999/JEIT170085
基金项目: 

国家自然科学基金(61401526),国家部委共用技术基金(9140A07020614DZ01)

Novel Track Coalescence Avoiding Joint Integrated Probabilistic Data Association Filter

Funds: 

The National Natural Science Foundation of China (61401526), The Foundation of National Ministries (9140A07020614DZ01)

  • 摘要: 针对联合综合概率数据关联算法(JIPDA)存在的航迹合并问题,将目标建模为随机有限集(RFS)提出改进的JIPDA算法。传统JIPDA首先产生初始概率密度函数(PDF),之后对该PDF进行近似来估计目标状态。为了使目标状态估计PDF与初始PDF之间的相似性最大化,当目标标签无意义时,提出对JIPDA的初始PDF进行优化。将KL散度作为相似性的衡量标准,建立起优化过程的代价函数。仿真实验表明,所提方法可有效地抑制传统JIPDA引起的航迹合并。
  • CHANG K C and BAR-SHALOM Y. Joint probabilistic data association for multitarget tracking with possibly unresolved measurements and maneuvers[J]. IEEE Transactions on Automatic Control, 1984, 29(7): 585-594. doi: 10.1109/TAC. 1984.1103597.
    MUICKI D and EVANS R. Joint integrated probabilistic data association-JIPDA[J]. IEEE Transactions on Aerospace and Electronic Systems, 2004, 40(3): 1093-1099. doi: 10.1109/ TAES.2004.1337482.
    尹帅, 袁俊泉, 吴顺华, 等. 一种改进的JIPDA多目标跟踪算法[J]. 雷达科学与技术, 2014, 12(3): 285-290. doi: 10.3969/ j.issn.1672-2337.2014.03.011.
    YIN Shuai, YUAN Junquan, WU Shunhua, et al. An improved JIPDA algorithm for multi-target tracking[J]. Radar Science and Technology, 2014, 12(3): 285-290. doi: 10.3969/j.issn.1672-2337.2014.03.011.
    伍明, 李琳琳, 魏振华, 等. 一种未知环境下机器人多目标跟踪算法[J]. 智能系统学报, 2015, 10(3): 448-453. doi: 10.3969/ j.issn.1673-4785.201405051.
    WU Ming, LI Linlin, WEI Zhenhua, et al. A robot multi- object tracking algorithm in unknown environments[J]. CAAI Transactions on Intelligent Systems, 2015, 10(3): 448-453. doi: 10.3969/j.issn.1673-4785.201405051.
    CHEN Xin, PELLETIER M, KIRUBARAJAN T, et al. Integrated Bayesian clutter estimation with JIPDA/MHT trackers[J]. IEEE Transactions on Aerospace and Electronic Systems, 2013, 49(1): 395-414. doi: 10.1109/TAES.2013. 6404111.
    BLOM H A P, BLOEM E A, and MUICKI D. JIPDA*: Automatic target tracking avoiding track coalescence[J]. IEEE Transactions on Aerospace and Electronic Systems, 2015, 51(2): 962-974. doi: 10.1109/TAES.2014.130327.
    MAHLER R. Statistical Multisource Multitarget Information Fusion[M]. London, Artech House, 2007: 5-14.
    WILLIAMS J L. Marginal multi-Bernoulli filters: RFS derivation of MHT, JIPDA and association-based MeMBer[J]. IEEE Transactions on Aerospace and Electronic Systems, 2015, 51(3): 1664-1687. doi: 10.1109/TAES.2015.130550.
    余艳. 融合KL散度和移地距离的高斯混合模型相似性度量方法[J]. 计算机应用, 2014, 34(3): 828-832. doi: 10.11772/j.issn. 1001-9081.2014.03.0828.
    YU Yan. Similarity measure method of Gaussian mixture model by integrating Kullback-Leibler divergence and earth mover's distance[J], Journal of Computer Applications, 2014, 34(3): 828-832. doi: 10.11772/j.issn.1001-9081.2014.03.0828.
    BLAHUT R E. Principles and Practice of Information Theory[M]. MA: Addison-Wesley, 1987, Chapter 7.
    SVENSSON L, SVENSSON D, and WILLETT P. Set JPDA algorithm for tracking unordered sets of targets[C]. 12th International Conference on Information Fusion, Seattle, WA, USA, 2009: 1187-1194.
    SCHUHMACHER D, VO B T, and VO B N. A consistent metric for performance evaluation of multi-object filters[J]. IEEE Transactions on Signal Processing, 2008, 56(8): 3447-3457. doi: 10.1109/TSP.2008.920469.
    MUICKI D and EVANS R. Clutter map information for data association and track initialization[J]. IEEE Transactions on Aerospace and Electronic Systems, 2004, 40(2): 387-398. doi: 10.1109/TAES.2004.1309992.
    JING P L, XU S Y, LI X, et al. Coalescence-avoiding joint probabilistic data association based on bias removal[J]. EURASIP Journal on Advances in Signal Processing, 2015(1): 1-13. doi: 10.1186/s13634-015-0205-2.
    PANAKKAL V P and VELMURUGAN R. Effective joint probabilistic data association using maximum a posteriori estimates of target states[C]. 16th International Conference on Information Fusion, Istanbul, Turkey, 2013: 781-788.
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出版历程
  • 收稿日期:  2017-01-23
  • 修回日期:  2017-07-17
  • 刊出日期:  2017-10-19

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