Target Type Recognition Algorithm for SAR Image Based on Multi-feature Fusion Classifier of KPFD

被引：0
|
作者：
Kong, Yingying [1 ]
Chen, Weiyang [1 ]
Leung, Henry [2 ]
机构：
[1] Nanjing Univ Aeronaut & Astronaut, Coll Informat Sci & Technol, Nanjing, Jiangsu, Peoples R China
[2] Univ Calgary, Dept Elect & Comp Engn, Calgary, AB, Canada
来源：
PROCEEDINGS OF 2015 IEEE 5TH INTERNATIONAL CONFERENCE ON ELECTRONICS INFORMATION AND EMERGENCY COMMUNICATION | 2015年
关键词：
SAR image; target recognition; Multi-feature fusion; PCA; decision level; measure level; KPCA;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Due to the presence of speckle, the target recognition algorithm of SAR image is different from other algorithms. There exists nuances in the detail of type recognition. This paper proposes Multi-feature fusion classifier of KPFD. Based on data from MSTAR database, the results of experiment show the new algorithm is more effective than other 5 kinds of recognition algorithm and recently recognition algorithm. In addition, when the KPFD recognition algorithm is combined with feature fusion classifier in the decision level and measure level, the feature fusion classifier brings good performance on the identification of the types of tank by using Naive Bayesian Classification algorithm(NBC). The recognition rate is up to 87%.
引用
收藏
页码：435 / 439
页数：5
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