Title :
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
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;
Conference_Titel :
Radar, 2006. CIE '06. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
0-7803-9582-4
Electronic_ISBN :
0-7803-9583-2
DOI :
10.1109/ICR.2006.343525
