PCA在雷达目标识别中的应用研究  

Application of PCA in radar target recognition

作　　者：杨进军[1] 文树梁[1] 

机构地区：[1]中国航天科工集团公司二院23所,北京100854

出　　处：《航天电子对抗》2007年第4期32-34,共3页Aerospace Electronic Warfare

摘　　要：研究了宽带高分辨雷达目标识别中的特征压缩问题。首先提取目标一维距离像双谱特征,然后应用主元分析法(PCA)降低目标特征维数,最后利用支持向量机对3类实测目标数据进行识别。实验结果表明,对雷达目标识别来讲,PCA是一种可行的特征压缩方法。The problem of feature compression in high-resolution radar target recognition is studied. Firstly the bispectrum features are extracted from the one-dimension range profiles of radar targets, and then Principal Component Analysis （PCA） is used to reduce the dimensionality of bispectrum features,lastly three kinds of real target echoes are classified by support vector machine. The experimental results demonstrate PCA is a feasible method of feature compression in radar target recognition.

关 键 词：雷达目标识别 PCA 双谱 特征压缩 

分 类 号：TN953[电子电信—信号与信息处理]