%0 Journal Article
%T Algorithm research of radar target recognition based on kernel principal component analysis<br>基于平移不变核主分量分析的雷达目标识别研究*
%A ZHAO Dong-bo
%A LI Hui
%A <br>赵东波
%A 李辉
%J 计算机应用研究
%D 2011
%I 
%X Kernel principal component analysis(KPCA) algorithm is a kind of important feature extraction algorithm about radar target recognition,but the shift sensitivity of radar target high range resolution profile(HRRP) has make KPCA has its shortcomings when it was used in radar target recognition system.This paper use zero phase representation to get shift-invariant HRRP,using KPCA in feature dimension compression,and proposed BP neural network classification algorithm to realize recognition.Based on themeasured...
%K kernel principal component analysis(KPCA)
%K zero phase representation(ZPR)
%K feature extraction
%K high range resolution profile(HRRP)
%K BP neural network(BPNN)<br>核主分量分析
%K 零相位表示法
%K 特征提取
%K 高分辨率距离像
%K BP神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=1F8EB868F38CE072B4E09B02B0023B67&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=F3090AE9B60B7ED1&sid=941C7B08AEDD1481&eid=F70C3F73C791247C&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=11