An improved fuzzy C-means cluster algorithm for radar data association

被引：0
作者：
Yu, Yang [1 ]
Zhang, Bingbing [1 ]
Rao, Bing [1 ]
Chen, Liang [1 ]
机构：
[1] School of Information Science and Engineering, Shenyang Ligong University, Shenyang
来源：
International Journal of Advancements in Computing Technology | 2012年 / 4卷 / 20期
关键词：
Curve moving target; Data association; Dynamic weight; Fuzzy C-means clustering; Track slope;
D O I：
10.4156/ijact.vol4.issue20.22
中图分类号：
学科分类号：
摘要：
The priori knowledge of the radar can not be used by the traditional fuzzy C-means clustering algorithm, which leads a poor accuracy of the data association. An improved fuzzy C-means clustering algorithm is proposed in this paper. The real-time change rate of the track slope of moving targets measured by radar is used to update the weight. Then the objective function of fuzzy C-means clustering algorithm is optimized by the dynamic weight based on the change rate of the slope to make sure the clustering center approximate to the actual value of the target, thus the accuracy of the data association is ensured. The simulation results show that the accuracy of the data association can be improved by the fuzzy C-means clustering algorithm based on the change rate of target track slope comparing with the traditional fuzzy C-means clustering algorithm.
引用
收藏
页码：181 / 189
页数：8
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