Title :
Application of feature extraction methods for landmine detection using the Wichmann/Niitek ground-penetrating radar
Author :
Zhu, Quan ; Collins, Leslie M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Duke Univ., Durham, NC, USA
Abstract :
Ground-penetrating radar (GPR) has been proposed as an alternative to classical electromagnetic induction techniques for the landmine detection problem. The Wichmann/Niitek system provides a good platform for novel GPR-based antitank mine detection and classification algorithm development due to its extremely high SNR. When the GPR sensor is mounted on a moving vehicle, the target signatures are hyperbolas in a time-domain data record. The goal of this work is to extract useful features that exploit this knowledge in order to improve target detection. The algorithms can be divided into two steps: feature extraction and classification. Preprocessing is also considered to remove both stationary effects and nonstationary drift of the data and to improve the contrast of the desired hyperbolas. The algorithm is evaluated using real data over primarily plastic antitank mines collected with a fielded GPR sensor at a government test site.
Keywords :
feature extraction; ground penetrating radar; image classification; landmine detection; radar imaging; remote sensing by radar; GPR sensor; GPR-based antitank mine detection; Wichmann/Niitek ground-penetrating radar; electromagnetic induction techniques; feature extraction methods; hyperbola; image classification; image preprocessing; landmine detection; nonstationary drift removal; stationary effect removal; target detection; target signatures; time-domain data; Classification algorithms; Data mining; Electromagnetic induction; Feature extraction; Ground penetrating radar; Landmine detection; Object detection; Radar detection; Time domain analysis; Vehicles;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2004.839431