摘要
针对多特征信息融合算法进行研究,给出了一种基于灰关联分析的多目标跟踪算法.该算法首先利用灰关联算法对多特征信息进行处理,然后利用证据距离法赋予各种特征信息不同的权重,进而利用D-S证据组合规则对多特征信息进行加权融合.将基于灰关联证据距离(GED)融合多特征信息的新算法与已有算法进行仿真对比,结果表明,本文所提新算法不仅具有较准确的目标跟踪精度,而且其时间花费较少.
Multi-feature information fusion algorithm is studied and a multi-target tracking algorithm based on grey relational analysis was proposed. Firstly, multi-feature information is processed by grey relational algorithm. Secondly, different weight of diversified characteristic information was assigned by using evidence distance. Finally, multi-feature information is given weighted fusion by use of D-S evidence combination rule. In comparison with the simulation results of existing algorithms, proposed the new algorithm for feature information based on grey relational evidence distance （GED） in this paper not only has target tracking precision ,but also costs less time. fusing multi- more accurate
作者
孙启臣
郭伟震
闫倩倩
周莉
SUN Qichen GUO Weizhen YAN Qianqian ZHOU Li(School of Information and Electrical Engineering, Ludong University, Yantai 264039, Chin)
出处
《鲁东大学学报（自然科学版）》
2017年第1期20-25,F0003,共7页
Journal of Ludong University:Natural Science Edition
基金
国家自然科学基金(61273152)
国家自然科学基金青年项目(61304052)
关键词
多特征信息融合
灰关联证据距离
熵权法
D-S证据组合规则
multi-feature information fusion
grey relational evidence distance
entropy weight method
D-S evidence combination rule
