杂波环境下基于全邻模糊聚类的联合概率数据互联算法

刘俊; 刘瑜; 何友; 孙顺

doi:10.11999/JEIT150849

杂波环境下基于全邻模糊聚类的联合概率数据互联算法

doi: 10.11999/JEIT150849

刘俊¹,
刘瑜²,
何友¹,
孙顺¹

1.
(海军航空工程学院信息融合研究所烟台 264001) ②(北京航空航天大学电子信息工程学院北京 100191)

基金项目:

国家自然科学基金(61471383)

计量
- 文章访问数: 1729
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- 被引次数: 0
出版历程
- 收稿日期: 2015-07-16
- 修回日期: 2016-03-08
- 刊出日期: 2016-06-19

Joint Probabilistic Data Association Algorithm Based on All-neighbor Fuzzy Clustering in Clutter

1.
(Research Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai 264001, China)

Funds:

The National Natural Science Foundation of China (61471383)

摘要

摘要: 针对杂波环境下的多目标跟踪数据互联问题，该文提出基于全邻模糊聚类的联合概率数据互联算法(Joint Probabilistic Data Association algorithm based on All-Neighbor Fuzzy Clustering, ANFCJPDA)。该算法根据确认区域中量测的分布和点迹-航迹关联规则构造统计距离，以各目标的预测位置为聚类中心，利用模糊聚类方法，计算相关波门内候选量测与不同目标互联的概率，通过概率加权融合对各目标状态与协方差进行更新。仿真分析表明，与经典的联合概率数据互联算法(Joint Probabilistic Data Association algorithm, JPDA)相比，ANFCJPDA较大程度地改善了算法的实时性，并且跟踪精度与JPDA相当。
- 多目标跟踪 /
- 多传感器 /
- 数据互联 /
- 模糊聚类
Abstract: This paper proposes a new Joint Probabilistic Data Association algorithm based on All-Neighbor Fuzzy Clustering (ANFCJPDA) for mutitarget tracking in the clutter. Firstly, distance measure is established according to measurements distribution in validation area and data correlation rules. Then, the predicted position is set up as a cluster center, and the association probabilities are calculated on the basis of fuzzy clustering, which are used as weights to update targets state and the covariance. Simulation results show that the proposed method reduces highly the computational complexity compared to conventional Joint Probabilistic Data Association (JPDA) technique, and is effective for multiple target tracking in a cluttered environment.
- Multiple target tracking /
- Multisensor /
- Data association /
- Fuzzy clustering

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参考文献(26)

SONG T L, KIM H W, and MUSICKI D. Iterative joint integrated probabilistic data association[C]. 16th International Conference on Information Fusion, Istanbul, Turkey, 2013: 1714-1720.

修建娟, 汪望松, 何友. 杂波环境下基于距离航速航向信息的多目标跟踪[J]. 系统工程与电子技术, 2014, 36(9): 1702-1706. doi: 10.3969/i.issn.1001-506X.2014.09.05.

XIU Jianjuan, WANG Wangsong, and HE You. Multiple target tracking in clutter based on distance speed and course[J]. Systems Engineering and Electronics, 2014, 36(9): 1702-1706. doi: 10.3969/i.issn.1001-506X.2014.09.05.

MUSICKI D and EVANS R. Multi-scan multi-target tracking in clutter with integrated track splitting filter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2009, 45(4): 1432-1447. doi: 10.1109/TAES.2007.4441748.

BARSHALOM Y and FORTMAN T E. Tracking and Data Association[M]. New York: Academic Press, 2011: 3-7.

PARK C, WOEHL T J, EVANS J E, et al. Minimum cost multi-way data association for optimizing multitarget tracking of interacting objects[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(3): 611-624. doi: 10.1109/TPAMI.2014.2346202.

AZIZ A M. A novel all-neighbor fuzzy association approach for tracking in a cluttered environment[J]. Signal Processing, 2011, 91: 2001-2015. doi: doi:10.1016/j.sigpro.2011.03.007.

BAE S H and YOON K J. Robust online multiobject tracking with data association and track management[J]. IEEE Transactions on Image Processing, 2014, 23(7): 2820-2833. doi: 10.1109/TIP.2014.2320821.

刘宗香, 谢维信, 黄敬雄. 一种新的基于概率理论的概率数据互联滤波器[J]. 电子与信息学报, 2009, 31(7): 1641-1645.

LIU Zongxiang, XIE Weixin, and HUNG Jingxiong. A new probabilistic data association filter based on probability theory[J]. Journal of Electronics Information Technology, 2009, 31(7): 1641-1645.

BLOM H, BLOEM E, and MUSICKI 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.

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: 1-5.

HE You, XIU Jianjuan, and GUAN Xin. Radar Data Processing with Applications[M]. 3rd ed. Beijing: Publishing House of Electronics Industry, 2013: 1-5.

AZIZ A M. A new nearest-neighbor association approach based on fuzzy clustering[J]. Aerospace Science and Technology, 2013, 26(1): 87-97. doi: 10.1016/j.ast.2012.02.017.

LI Z, CHEN J, GU Y, et al. Small moving infrared space target tracking algorithm based on probabilistic data association filter[J]. Infrared Physics and Technology, 2014, 63: 84-91. doi: 10.1016/j.infrared.2013.12.003.

LI Wenling and JIA Yingmin. Distributed interacting multiple model HN filtering fusion for multiplatform maneuvering target tracking in clutter[J]. Signal Processing, 2010, 90(5): 1655-1668. doi: 10.1016/j.sigpro.2009.11.016.

KHALEGHI B, KHAMIS A, KARRAY F O, et al. Multisensor data fusion: A review of the state-of-the-art[J]. Information Fusion, 2013, 14(1): 28-44. doi: 10.1016/j.inffus. 2011.08.001.

张俊根, 姬红兵, 蔡绍晓. 基于高斯粒子JPDA滤波的多目标跟踪算法[J]. 电子与信息学报, 2010, 32(11): 2686-2690. doi: 10.3724/SP.J.1.1146.2009.01549.

ZHANG Jungen, JI Hongbing, and CAI Shaoxiao. Gaussian particle JPDA filter based multi-target tracking[J]. Journal of Electronics Information Technology, 2010, 32(11): 2686-2690. doi: 10.3724/SP.J.1.1146.2009.01549.

JIANG X, HARISHAN K, THAMARASA R, et al. Integrated track initialization and maintenance in heavy clutter using probabilistic data association[J]. Signal Processing, 2014, 94: 241-250. doi: 10.1016/j.sigpro.2013.06. 026.

KIM T H, MUSICKI D, SONG T L, et al. Smoothing joint integrated probabilistic data association[J]. IET Radar, Sonar Navigation, 2014, 9(1): 62-66. doi: 10.1049/iet-rsn. 2013.0347.

ZHOU B and BOSE N K. Multitarget tracking in clutter: fast algorithms for data association[J]. IEEE Transactions on Aerospace and Electronic Systems, 1993, 29(2): 352-363. doi: 10.1109/7.210074.

ROECHER J A and PHILLIS G L. Suboptimal joint probabilistic data association[J]. IEEE Transactions on Aerospace Electronics Systems, 1993, 29(2): 510-517. doi: 10.1109/7. 210087.

SVENSSON D, ULMKE M, and HAMMARSTRAND L. Multitarget sensor resolution model and joint probabilistic data association[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(4): 3418-3434. doi: 10.1109/ TAES.2012.6324722.

HABTEMARIAN B, THARMARASA R, THAYAPARAN T, et al. A multiple-detection joint probabilistic data association filter[J]. IEEE Journal of Selected Topics in Signal Processing, 2013, 7(3): 461-471. doi: 10.1109/JSTSP.2013.2256772.

Li L and XIE W. Intuitionistic fuzzy joint probabilistic data association filter and its application to multitarget tracking [J]. Signal Processing, 2014, 96: 433-444. doi: 10. 1016/j. sigpro.2013.10.011.

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