[1]陈志仁,顾 红.基于注水原理的雷达目标多分类器集成算法[J].南京理工大学学报(自然科学版),2018,42(03):380.[doi:10.14177/j.cnki.32-1397n.2018.42.03.019]
 Chen Zhiren,Gu Hong.Radar target multi-classifier integration algorithm based on water-filling theory[J].Journal of Nanjing University of Science and Technology,2018,42(03):380.[doi:10.14177/j.cnki.32-1397n.2018.42.03.019]
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基于注水原理的雷达目标多分类器集成算法
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
42卷
期数:
2018年03期
页码:
380
栏目:
出版日期:
2018-06-30

文章信息/Info

Title:
Radar target multi-classifier integration algorithm based on water-filling theory
文章编号:
1005-9830(2018)03-0380-05
作者:
陈志仁顾 红
南京理工大学 电子工程与光电技术学院,江苏 南京 210094
Author(s):
Chen ZhirenGu Hong
School of Electronic and Optical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China
关键词:
注水原理 雷达目标 多分类器 融合系数矩阵
Keywords:
water-filling theory radar targets multi-classifiers fusion coefficient matrix
分类号:
TN957.51
DOI:
10.14177/j.cnki.32-1397n.2018.42.03.019
摘要:
为了克服单一分类器的性能限制,通过集成不同分类器获得更高的雷达目标分类性能。在利用训练样本获得不同目标特征以及不同分类器的分类性能的基础上,根据注水原理计算出多个分类器集成的融合系数矩阵。对输出的判决系数矩阵设置判决阈值。实测雷达数据的实验结果表明,该文方法的平均识别率达到了87.68%。
Abstract:
Different classifiers are integrated to overcome the performance limitation of a single classifier and obtain higher performance of radar target classification. According to different target features and different classification performances of each classifier obtained by training samples,a fusion coefficient matrix of different classifiers integration is calculated based on the water-filling theory. A decision threshold is set for the output coefficient matrix. Experimental results of measured radar data show that the average recognition rate of the proposed method is 87.68%.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2017-11-08 修回日期:2018-01-05
基金项目:国家自然科学基金(61471198; 61671246)
作者简介:陈志仁(1986-),男,博士生,主要研究方向:雷达信号处理、目标识别,E-mail:chenzhiren1986@126.com; 通讯作者:顾红(1967-),男,博士,教授,主要研究方向:噪声雷达、高速目标探测、MIMO雷达信号处理,E-mail:gh_njust@163.com。
引文格式:陈志仁,顾红. 基于注水原理的雷达目标多分类器集成算法[J]. 南京理工大学学报,2018,42(3):380-384.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2018-06-30