首页 | 本学科首页   官方微博 | 高级检索  
     

低分辨雷达的目标特征提取方法
引用本文:王伟,张汉华,姜卫东,聂镭,陈曾平. 低分辨雷达的目标特征提取方法[J]. 国防科技大学学报, 2002, 24(2): 31-35
作者姓名:王伟  张汉华  姜卫东  聂镭  陈曾平
作者单位:国防科技大学电子科学与工程学院,湖南,长沙,410073
基金项目:国家部委预研项目资助 (4 13 0 3 0 4 0 1)
摘    要:基于现役低分辨警戒雷达 ,研究了进行目标分类和识别的途径 ,提出了基于波形特征和时间谱信息的目标分类和识别方法 ,试验分析了基于目标波形信息的特征 ,得出目标波形信息可用于目标识别的结论。现场试验表明 ,该方法对目标大小分类和架次识别有好的效果。

关 键 词:低分辨  雷达  波形  特征提取  目标识别
文章编号:1001-2486(2002)02-0031-05
收稿时间:2001-09-13
修稿时间:2001-09-13

The Study of Target Feature Extracting Method Based on Low-Resolution Radar
WANG Wei,ZHANG Hanhu,JIANG Weidong,NIE Lei and CHEN Zengping. The Study of Target Feature Extracting Method Based on Low-Resolution Radar[J]. Journal of National University of Defense Technology, 2002, 24(2): 31-35
Authors:WANG Wei  ZHANG Hanhu  JIANG Weidong  NIE Lei  CHEN Zengping
Affiliation:College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China;College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China;College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China;College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China;College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China
Abstract:Based on the active service low-resolution radar,the approach to target classification and recognition is studied The methods of target classification and recognition are proposed according to the information of target waveforms and time-spectrum The feature extracted by target waveform is analyzed and the useful conclusion is given The experiment result demonstrates that this recognition method is fine to classify big and small aircraft and recognize single plane and multiple planes
Keywords:low-resolution:radar  waveform  feature extracting target recognition
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《国防科技大学学报》浏览原始摘要信息
点击此处可从《国防科技大学学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号