红外与毫米波学报2011，Vol.30Issue(6)：566-570,5.
一种基于时频原子特征的雷达辐射源信号识别方法
A method for radar emitter signal recognition based on time-frequency atom features
摘要
Abstract
A novel method for radar emitter signal recognition based on time-frequency atom feature is presented. During training, based on the over-complete time-frequency atom dictionary, a few atoms which can separate different kinds of signals best are extracted as a set of fixed feature according to the class separability. During testing, the module of inner product between atoms and signals is used as the input feature for the fuzzy ARTMAP classifier, and the radar emitter signals can be recognized automatically. Experimental results of five kinds of typical radar emitter signals show that this method reduces the computational amount of feature extraction during testing obviously, and the input features have strong concentration within classes and large separability between classes. Our method can achieve high recognition accuracy at the SNR larger than 3 Db.关键词
雷达辐射源/特征提取/时频原子/类区分度/模糊自适应共振网络Key words
radar emitters/ feature extraction/ time-frequency atom/ class separability/ fuzzy ARTMAP分类
信息技术与安全科学引用本文复制引用
王希勤,刘婧瑶,孟华东,刘一民..一种基于时频原子特征的雷达辐射源信号识别方法[J].红外与毫米波学报,2011,30(6):566-570,5.基金项目
973项目(2010CB731901) （2010CB731901）
国家自然科学基金(40901157) （40901157）
