Landmine detection using forward-looking ground penetrating radar

Abstract

Landmine detection using radar is a very challenging problem due to weak signal returns of landmines and extremely complicated surveying environments. In this paper, we present a new landmine detection system using forward-looking ground penetrating radar (FLGPR), which has shown a promising result in a recently conducted blind test. The system uses wavelet packet transform and the sequential feature selection algorithm to extract the most discriminant information distributed in the joint time-frequency domain for detecting landmines. We also propose a cascade training method that allows a WPT based detector to continue learning from the errors made on the unseen environment to improve its detection performance. The effectiveness of the proposed detector is demonstrated through a blind test based on the measured FLGPR data collected over an area of 14400 square meters.