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。
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.
出处
《海军航空工程学院学报》
2013年第1期25-28,共4页
Journal of Naval Aeronautical and Astronautical University
关键词
类云模型
C均值聚类
航迹关联
cluster cloud model
c-means clustering
track association
