学术
摘 要:
决策层融合目标识别本质上是一个不确定性信息处理问题，该文基于灰色系统理论中的灰色定权聚类方法提出了一种新的决策层融合目标识别算法。该算法将一个M类目标识别问题转化为M个两类目标识别问题，然后对每个两类识别问题采用灰色定权聚类的方法解决，其中白化权函数通过训练样本学习确定。利用该算法对3种分类器识别5类雷达目标的结果进行融合，实验结果表明该方法能有效提高目标识别性能。[著者文摘]
文章出处:
《电子与信息学报》-2008年30卷2期 -255-258页
栏目信息:
分 类 号:
文献标识码:
A
文章编号:
1009-5896（2008）02-0255-04
A Method of Decision Fusion for Target Recognition Based on Grey Fixed Weight Clustering
Jia Yu-ping, Li Ya-nan, Fu Yao-wen （ ATR Lab. of National University of Defense Technology Zhuang Zhao-wen Changsha 410073, China）
Abstract:
The problem of decision fusion for target recognition is usually solved by the uncertainty information processing methods. This paper presents a novel algorithm of decision fusion for target recognition based on the grey fixed weight clustering analysis. The problem of recognizing M classes target is transformed into M problems of recognizing two classes target, and then each problem of recognizing two classes target is solved by the grey fixed weight clustering. The whitenization weight functions of each two classes are assessed by training samples. The experiment conducted on three classifiers and five classes＇ radar target data demonstrates this method can effectively improve the recognition performance.[著者文摘]
Key words:
Target recognition; Grey fixed weight clustering; Whitenization weight function; Information fusion
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