FEATURE EXTRACTION IN THROUGH-THE-WALL RADAR IMAGING

被引：4

作者：

Debes, Christian ^{[1
]}

Hahn, Juergen ^{[1
]}

Zoubir, Abdelhak M. ^{[1
]}

Amin, Moeness G. ^{[2
]}

机构：

[1] Tech Univ Darmstadt, Signal Proc Grp, Darmstadt, Germany

[2] Villanova Univ, Ctr Adv Commun, Villanova, PA 19085 USA

来源：

2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING | 2010年

关键词：

Through-the-Wall; radar imaging; feature extraction; superquadrics; classification; TARGET DETECTION;

D O I：

10.1109/ICASSP.2010.5495929

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper deals with the problem of automatic target classification or Through-the-Wall radar imaging. The proposed scheme considers stationary objects in enclosed structures and works on the SAR image rather than the raw data. It comprises segmentation, feature extraction based on superquadrics, and classification. We present a recursive splitting tree to obtain optimum parameters for feature extraction. Support vector machines and nearest neighbor classifiers are then applied to successfully classify among different indoor targets. The classification methods are tested and evaluated using real data generated from synthetic aperture Through-the-Wall radar imaging experiments.

引用

页码：3562 / 3565

页数：4

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