基于直觉模糊c均值聚类核匹配追踪的弹道中段目标识别方法

doi:10.3969/j.issn.1000-436x.2012.11.017

Abstract

Abstract:

Kernel matching pursuit requires every step of searching process be global optimal searching in the redundant dictionary of function.Namely,the dictionary learning time of KMP was too long.To the above drawbacks,a novel technique for KMP based on IFCM was proposed to substitute local searching for global searching by the property superiority of dynamic clustering performance,which was also the superiority in Intuitionistic fuzzy c-means algorithm.Then two testing including classification and effectiveness were carried out towards four real sample data.Subsequently,high resolution range profile (HRRP)was selected from the classical properties of target recognition in e middle ballistic trajectory,which were extracted for getting sub-range profile.Finally,three algorithms including FCM,KMP,IFCM-KMP were carried out respectively towards different kinds of sub-range profile samples in emulation platform,the conclusion of which fully demonstrates that the IFCM-KMP algorithm is superior over FCM and KMP when it comes to target recognition in the middle ballistic trajectory.

Key words: intuitionistic fuzzy sets, c-means clustering, fuzzy c-means clustering, kernel matching pursuit, high resolution range profile, target recognition

Yang LEI,Wei-wei KONG,Ying-jie LEI. Technique for target recognition based on intuitionistic fuzzy c-means clustering and kernel matching pursuit[J]. Journal on Communications, 2012, 33(11): 136-143.

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数据集	FCM	KMP	IFCM-KMP
Iris	0.072 1	0.05 39	0.031 1
Wine	0.065 2	0.048 4	0.031 2
Wisconsin	0.074 4	0.045 8	0.032 3
Motorcycle	0.068 9	0.050 4	0.028 8

性能指标	FCM	KMP	IFCM-KMP
PC	0.647 8	0.789 1	0.852 0
CE	0.643 3	0.332 4	0.852 1
SC	1.897 0	1.666 6	1.575 0
S	0.007 7	0.010 1	0.013 1
XB	3.111 0	2.841 2	2.110 1
DI	0.033 0	0.012 2	0.048 0
ADI	0.035 1	0.013 3	0.049 6

算法	平均错分误差e’	平均识别率?	平均识别速度s
FCM	0.755	0.481	0.800
KMP	0.381	0.773	12.100
IFCM-KMP	0.241	0.867	3.211

Technique for target recognition based on intuitionistic fuzzy c-means clustering and kernel matching pursuit

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