Synthetic Aperture Radar Imaging System for Landmine Detection Using a Ground Penetrating Radar on Board a Unmanned Aerial Vehicle

• Published in: IEEE access Vol. 6; pp. 45100 - 45112
• Main Authors: Garcia Fernandez, Maria, Alvarez Lopez, Yuri, Arboleya Arboleya, Ana, Gonzalez Valdes, Borja, Rodriguez Vaqueiro, Yolanda, Las-Heras Andres, Fernando, Pino Garcia, Antonio
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-01-2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Clutter; drones; Ground penetrating radar; Ground penetrating radar (GPR); Image resolution; Inspection; Land mine removal; Land mines; Landmine detection; Mine detection; Mine detectors; Object recognition; Radar; Radar imaging; Radar measurement; Radar polarimetry; real time kinematic (RTK); Soil; Soils; subsurface sensing and imaging; Synthetic aperture radar; synthetic aperture radar (SAR); unmanned aerial vehicle (UAV); Unmanned aerial vehicles
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2018.2863572

This paper presents a novel system to obtain images from the underground based on ground penetrating radar (GPR). The proposed system is composed by a radar module mounted on board an unmanned aerial vehicle (UAV), which allows the safe inspection of difficult-to-access areas without being in direct contact with the soil. Therefore, it can be used to detect dangerous buried objects, such as landmines. The radar measurements are coherently combined using a synthetic aperture radar (SAR) algorithm, which requires cm-level accuracy positioning system. In addition, a clutter removal technique is applied to mitigate the reflection at the air-soil interface (which is caused by impedance mismatching). Besides the aforementioned advantages, the system can detect both metallic and dielectric targets (due to the use of a radar instead of a metal detector) and it allows to obtain high-resolution underground images (due to the SAR processing). The algorithms and the UAV payload are validated with measurements in both controlled and real scenarios, showing the feasibility of the proposed system.