基于直觉模糊聚类的数据关联算法

Data association algorithm based on intuitionistic fuzzy clustering

针对多传感器观测数据存在不确定性的问题,基于直觉模糊聚类,提出一种新的数据关联算法。将改进的直觉模糊C-均值聚类(IFCM)算法应用于数据关联,首先将观测数据和预测数据进行直觉模糊化,然后计算直觉模糊集之间的加权距离以获得观测与航迹的隶属度,最后依次搜索最大隶属度实现观测与航迹的关联。仿真实验表明,存在模糊观测数据情况下,算法能有效地进行数据关联。

To deal with the uncertainty of multi-sensor observations, a new data association algorithm based on intuitionistic fuzzy clustering was proposed. The clustering algorithm of improved Intuitionistic Fuzzy C-Means （IFCM） was applied to data association in the proposed algorithm. Firstly, the observed data and predicted data were made to be intuitionistic fuzzy. Then the weighted distance between intuitionistic fuzzy sets was calculated to acquire membership degrees of observation and track. Finally, the highest degree of membership was sought successively to associate observation and track. The simulation results show that the presented algorithm can associate data with the fuzzy observations effectively.