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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。
Aiming at the characteristics of multisensor multi-target trajectory association, this paper proposes a joint solution of class cloud model and c-means clustering for trajectory association. The parameters which characterize the trajectory are constructed into the cluster center and the sample space to be classified. The cloud-based model and the c-means clustering algorithm are used to classify and converge the trajectories from different sensors. The c-mean The clustering track association model effectively solves the problem of track association in a target-intensive environment. The simulation results show the effectiveness and robustness of the proposed algorithm.