Feature Extraction from GPR Data for Identification of Landmine-Like Objects Under Rough Ground Surface

Abstract

Feature extraction from ground penetrating radar (GPR) data for identification of landmine-like objects under rough ground surface is studied. The feature proposed here is a time interval between two pulses reflected from top and bottom sides of landmine-like objects. Since the time interval is closely related to the thickness and permittivity of the objects, it is expected that this feature is suitable for target identification. Monte Carlo simulations using data set generated by an FDTD method show that good identification performance is obtained and that this feature is suitable for discrimination of landmines from confusing clutter objects.