Presentation + Paper
27 May 2022 Analysis of buried target and clutter signature in ground penetrating radar imaging
Traian V. Dogaru, Brian Phelan, Colin Kelly
Author Affiliations +
Abstract
The US Army Combat Capabilities Development Command Army Research Laboratory (DEVCOM ARL) is currently developing unmanned aerial vehicle (UAV)-based radar imaging technology for counter-explosive hazard (CEH) applications. The explosive hazards under consideration include landmines, improvised explosive devices, and other closeto-ground-surface targets, which have long posed major detection challenges to any kind of sensors. Since many of these targets are buried underground, ground penetrating radar (GPR) imaging has emerged as one of the technologies holding great promise to solve this problem. In this paper, we consider UAV-based synthetic aperture radar (SAR) configurations capable of creating 2-D or 3-D images of underground targets, with both down-looking and side-looking sensing geometries. The clutter produced by rough ground surface and soil permittivity fluctuations is characterized via numerical simulations, with the purpose of evaluating the target-to-clutter ratio (TCR), which is the first indicator of detection performance in clutter-limited radar systems. For down-looking geometries, we compare the TCR performance of 2-D and 3-D imaging systems, as a function of target burial depth. For side-looking geometries, we compare the TCR in 2-D radar images created in the ground plane and underground vertical planes. The results of this analysis demonstrate that the 3-D down-looking GPR imaging system outperforms all the other configurations by a large margin.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Traian V. Dogaru, Brian Phelan, and Colin Kelly "Analysis of buried target and clutter signature in ground penetrating radar imaging", Proc. SPIE 12108, Radar Sensor Technology XXVI, 1210804 (27 May 2022); https://doi.org/10.1117/12.2621021
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KEYWORDS
Radar

Imaging systems

3D image processing

Radar imaging

Synthetic aperture radar

Target detection

Scattering

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