Robust PCA Micro-Doppler Classification Using SVM on Embedded Systems

被引：80

作者：

Zabalza, Jaime ^{[1
]}

Clemente, Carmine ^{[1
]}

Di Caterina, Gaetano ^{[1
]}

Ren, Jinchang ^{[1
]}

Soraghan, John J. ^{[1
]}

Marshall, Stephen ^{[1
]}

机构：

[1] Univ Strathclyde, Ctr Excellence Signal & Image Proc, Glasgow, Lanark, Scotland

来源：

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 2014年 / 50卷 / 03期

基金：

英国工程与自然科学研究理事会;

关键词：

RADAR; SIGNATURES;

D O I：

10.1109/TAES.2014.130082

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

In this paper, a novel feature extraction technique for micro-Doppler classification and its real-time implementation using a support vector machine classifier on a low-cost, embedded digital signal processor are presented. The effectiveness of the proposed technique is improved through exploitation of the outlier rejection capabilities of robust principal component analysis (PCA) in place of classic PCA.

引用

页码：2304 / 2312

页数：9

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