基于支持向量机的窄带雷达弹道导弹目标识别技术  

Narrowband Radar Ballistic Missile Target Recognition Technology Based on SVM

作　　者：魏文博[1] 蔡红军[1] 

机构地区：[1]中国电子科技集团公司第38研究所,安徽合肥230088

出　　处：《电子科技》2016年第6期75-78,共4页Electronic Science and Technology

基　　金：国家高技术研究发展计划"863"基金项目(2014AA7052010)

摘　　要：窄带雷达由于受到带宽限制,无法获取到目标高分辨精细识别信息,仅能通过目标轨道运动特征和窄带RCS特征对目标属性进行初步分类识别,文中基于支持向量机分类算法,从窄带雷达回波数据中提取弹头群和弹体群目标的特征,实现了弹道导弹群目标初步分类识别。在对弹头群和弹体群分类识别的基础上,窄带雷达可集中更多的时间和能量资源重点对弹头群类目标进行跟踪,并为后续宽带目标识别雷达提供重点目标位置信息。Subject to radar bandwidth,the narrowband radar can＇t obtain the information of high-resolution structure of targets. In case of the narrowband radar,targets are classified only by characteristics of orbital motion and Rradar Cross Section（ RCS）. In this paper,characteristics of missile warhead group and body group are extracted,and missile targets from a narrowband radar experiment data are classified using Support Vector Machine（ SVM）. After classification of missile warhead group and body group,the narrowband radar can track missile warhead group using more time and energy. In the meantime,the location of the main target can provide for broadband identification radar.

关 键 词：支持向量机 窄带 目标识别 雷达 弹道导弹 

分 类 号：TN958[电子电信—信号与信息处理]