幅度谱差分子空间雷达自动目标识别  

Radar Auomatic Target Recognition in Amplitude Spectrum Difference Subspace

作　　者：刘敬[1] 

机构地区：[1]西安邮电学院电子工程学院,西安710121

出　　处：《现代雷达》2012年第8期38-41,45,共5页Modern Radar

基　　金：国家自然科学基金(61003199);中央高校基本科研业务费专项资金(K50510020015);陕西省教育厅自然科学专项基金(2010JK821);西安邮电学院博士启动基金(000-1271)资助课题

摘　　要：雷达高分辨距离像是目标的重要结构特征,其维数通常很高,造成数据可分性表达差,识别过程计算复杂度高,识别率低。为降低距离像的维数,提出一种新的距离像特征提取方法,即采用直接线性判别分析(dLDA)在距离像幅度谱差分空间进行特征提取,得dLDA幅度谱差分子空间。目标识别即在所得dLDA幅度谱差分子空间中进行。采用外场实测数据,分别训练了最小距离分类器和one-against-all支撑向量机分类器,2种分类器的识别结果均表明,该方法可显著地降低数据维数并提高识别率。Radar high resolution range profile （HRRP） is an important type of target structure feature. The dimensionality of HRRP is very high, which results in poor data diseriminant representation, high recognition computation complexity, and low recognition rate. In order to reduce the dimensionality of HRRP, a novel HRRP feature extraction method is presented, i.e. , direct linear dis- criminant analysis（dLDA） is used to perform feature extraction in the amplitude spectrum difference space of HRRP, and a dLDA amplitude spectrum difference subspace is obtained. Target recognition is implemented in the resulting dLDA amplitude spectrum difference subspace. Shortest distance classifier and one-against-all support vector machine （ SVM ） classifier arc designed to evalu- ate the recognition performance. Experimental results for measured data show that the presented method reduces data dimensionality greatly and improves recognition rate remarkably.

关 键 词：雷达自动目标识别 幅度谱差分子空间 直接线性判别分析 特征提取 高分辨距离像 

分 类 号：TN957.52[电子电信—信号与信息处理]