A GPR-based landmine identification method using energy and dielectric features

Alper Genç; Gözde Bozdaği Akar

doi:10.1117/12.2301009

30 April 2018 A GPR-based landmine identification method using energy and dielectric features

Alper Genç, Gözde Bozdaği Akar

Proceedings Volume 10628, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII; 1062809 (2018) https://doi.org/10.1117/12.2301009
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

Abstract

This study presents a novel landmine identification method that estimates intrinsic parameters of buried objects from their primary and secondary GPR reflections to reduce false alarm rates of GPR-based landmine detection algorithms. To achieve this, two different features are extracted from A-scan GPR data of buried objects. The first feature identifies significant GPR signal length. The second feature estimates intrinsic impedance of the object. These two features are classified with support vector machine (SVM) classifier. The experimental results show that the proposed features have very high discrimination power which reduces false alarm rates to a great extent.

Conference Presentation

Citation Download Citation

Alper Genç and Gözde Bozdaği Akar "A GPR-based landmine identification method using energy and dielectric features", Proc. SPIE 10628, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII, 1062809 (30 April 2018); https://doi.org/10.1117/12.2301009

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