CAJ | 학술논문

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.
침대다전감기다목표항적관련적특점,제출료장류운모형화c균치취류연합응용우항적관련적해결방법.장표정항적특정적삼량구성취류중심화대분류적양본공간,이용류운모형화c균치취류산법대래자불동전감기적항적진행분류화수렴판단,구건료기우류운모형적c균치취류항적관련모형,유효지해결료목표밀집배경하적항적관련문제,통과방진연구설명료해산법적유효성화로봉성.
A method of track association using both cluster cloud model and c-means clustering was put forward according to the features of multi-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.