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基于类云模型的c均值聚类航迹关联算法
引用本文:车志宇,吴媛媛.基于类云模型的c均值聚类航迹关联算法[J].海军航空工程学院学报,2013,28(1):25-28.
作者姓名:车志宇  吴媛媛
作者单位:1. 海军航空工程学院电子信息工程系,山东烟台264001
2. 海军北海舰队司令部,山东青岛266071
摘    要:针对多传感器多目标航迹关联的特点,提出了将类云模型和c均值聚类联合应用于航迹关联的解决方法。将表征航迹特征的参量构成聚类中心和待分类的样本空间,利用类云模型和c均值聚类算法对来自不同传感器的航迹进行分类和收敛判断,构建了基于类云模型的c均值聚类航迹关联模型,有效地解决了目标密集环境下的航迹关联问题,通过仿真研究说明了该算法的有效性和鲁棒性。

关 键 词:类云模型  c均值聚类  航迹关联

C-means Clustering Track Correlation Algorithm Based on Cluster Cloud Model
CHE Zhi-yu and WU Yuan-yuan.C-means Clustering Track Correlation Algorithm Based on Cluster Cloud Model[J].Journal of Naval Aeronautical Engineering Institute,2013,28(1):25-28.
Authors:CHE Zhi-yu and WU Yuan-yuan
Institution:1.Department of Electronic and Information Engineering,NAAU,Yantai Shandong 264001,China;2.Headquarters of Beihai Fleet,Qingdao Shandong 266071,China)
Abstract:A method of track association using both cluster cloud model and c-means clustering was put forward according to the features of muhi-sensor multi-target track association. The clustering center and sample space with the parameters of track features was constructed, with the method of cluster cloud model and c-means clus- tering, sorting tracks from different sensors and judging whether they were convergent. And a track association model with cluster cloud model and c-means clustering is built, solving the track association problem in the presence of dense targets effectively. The effectivity and robustiness of the algorithm is proved through simulation.
Keywords:cluster cloud model  c-means clustering  track association
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