Aspect-invariant feature extraction and associated landmine detector in UWB SAR

Author

Tian, Jin ; Zhi-Min, Zhou ; Wen-ge, Chang ; Qian, Song

Author_Institution

Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha

fYear

2006

fDate

16-19 Oct. 2006

Firstpage

1

Lastpage

4

Abstract

Vehicle- or air-borne ultra-wide band synthetic aperture radar (UWB SAR) can perform landmine detection over large areas, where too many false alarms is the major problem for UWB SAR application in practice. In this paper, landmine aspect-invariant feature extraction using the space-wavenumber distribution (SWD) and its associated support vector machine (SVM) with a hypersphere classification boundary are proposed in landmine detection procedure. The proposed methods have been tested by the real data collected with the rail-GPSAR system

Keywords

feature extraction; ground penetrating radar; landmine detection; radar imaging; support vector machines; synthetic aperture radar; ultra wideband radar; SVM; SWD; UWB SAR; aspect-invariant feature extraction; ground penetrating radar; hypersphere classification boundary; landmine detection procedure; rail-GPSAR system; space-wavenumber distribution; support vector machine; ultra-wide band synthetic aperture radar; Azimuth; Clutter; Detectors; Feature extraction; Landmine detection; Radar detection; Reflectivity; Support vector machine classification; Support vector machines; Synthetic aperture radar; Ultra-wide band; hypersphere support vector machine; space-wavenumber distribution; synthetic aperture radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar, 2006. CIE '06. International Conference on

Conference_Location

Shanghai

Print_ISBN

0-7803-9582-4

Electronic_ISBN

0-7803-9583-2

Type

conf

DOI

10.1109/ICR.2006.343525

Filename

4148206