Wavelet-based shape feature extraction for GPR detection of nonmetallic antipersonnel land mines

John W. Brooks

doi:10.1117/12.396188

22 August 2000 Wavelet-based shape feature extraction for GPR detection of nonmetallic antipersonnel land mines

John W. Brooks

Proceedings Volume 4038, Detection and Remediation Technologies for Mines and Minelike Targets V; (2000) https://doi.org/10.1117/12.396188
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

This paper describes a novel approach to detecting shape features of non-metallic anti-personnel land mine using certain attributes of wavelet packets and wavelets in general. Data sources included 2GHz and 10 GHz pulse ground penetrating radar (GPR) data, and 6 GHz stepped-frequency GPR data, from laboratory measurements. Targets are chosen to include rocks and other non-lethal clutter which normally present false alarms to the GPR. The GPR signals are first de-noised with an adaptive wavelet packet de-noising method, then the shape features of the APL are determined form exploiting the regularity properties of wavelets. Results are shown which indicate that the method may be applied to pulse GPR processing, but not for frequency-stepped GPRs. Preprocessing the GPR signal for clutter reduction may not always be necessary, thus simplifying the detection process.

Citation Download Citation

John W. Brooks "Wavelet-based shape feature extraction for GPR detection of nonmetallic antipersonnel land mines", Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, (22 August 2000); https://doi.org/10.1117/12.396188

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