Robust PCA micro-doppler classification using SVM on embedded systems

Author

Zabalza, Jaime ; Clemente, Carmine ; Di Caterina, Gaetano ; Jinchang Ren ; Soraghan, John J. ; Marshall, Stephen

Author_Institution

Centre for Excellence in Signal & Image Process., Univ. of Strathclyde, Glasgow, UK

Volume

50

Issue

3

fYear

2014

fDate

Jul-14

Firstpage

2304

Lastpage

2310

Abstract

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.

Keywords

Doppler radar; digital signal processing chips; embedded systems; feature extraction; image classification; image motion analysis; principal component analysis; radar imaging; support vector machines; PCA; SVM; embedded digital signal processor; embedded systems; feature extraction technique; microDoppler classification; outlier rejection capabilities; principal component analysis; support vector machine classifier; Digital signal processing; Doppler radar; Feature extraction; Principal component analysis; Support vector machines;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2014.130082

Filename

6965776