Imaging Modes for Ground Penetrating Radar and Their Relation to Detection Performance

Abstract

The focus of this paper is an empirical study conducted to determine how imaging modes for ground penetrating radar (GPR) affect buried object detection performance. GPR data were collected repeatedly over lanes whose buried objects were mostly nonmetallic. This data were collected and processed with a GPR antenna array, system hardware, and processing software developed by the authors and their colleagues. The system enables GPR data to be collected, imaged, and processed in realtime on a moving vehicle. The images are focused by applying multistatic and synthetic aperture imaging techniques either separately or jointly to signal scans acquired by the GPR antenna array. An image-based detection statistic derived from the ratio of buried object energy in the foreground to energy of soil in the background is proposed. Detection-false alarm performance improved significantly when the detection algorithm was applied to focused multistatic synthetic aperture radar (SAR) images rather than to unfocused GPR signal scans.Index Terms-Ground penetrating radar (GPR), multistatic imaging, synthetic aperture radar (SAR).

Detection and Identification of Remnant PFM-1 ‘Butterfly Mines’ with a UAV-Based Thermal-Imaging Protocol

“…Furthermore, because radar waves are sensitive to dielectric constant variations of the subsurface, GPR can be used to classify buried objects and characterize soil properties [23][24][25]. However, a number of limitations of GPR surveys in application to landmine detection have also emerged, including prohibitive false alarm rates and prolonged acquisition and processing times needed to collect non-aliased 3D datasets required for identification of smaller landmines [18,26]. In a recent study, focused specifically on GPR-based detection of PFM-1 landmine targets, Lombardi et al [22] demonstrated that under laboratory conditions, which featured direct sensor contact with the ground surface, optimal landmine orientation and soil properties, high-resolution GPR could not reliably identify the characteristic shape of the PFM-1 and reliably detect or classify this MEC type.…”

Dependence of landmine radar signature on aspect angle

“…Target detection and discrimination algorithms that perform robustly across different terrain and over many possible objects often require multiple scans. Sensor false alarm rate can be reduced if spatial features and geometrical information can be extracted, and this needs a properly acquired image of the subsurface [18][19][20][21]. The latter weakness is related to the ability to potentially map any dielectric anomaly, which could generate a large number of misleading detections [22].…”

Ballistic Ground Penetrating Radar Equipment for Blast-Exposed Security Applications

“…However, standalone GPR platforms for antipersonnel landmine detection are less common than their metal detector counterparts [21], a situation possibly related to the fact that GPR signal interpretation remains a complex task, and that the mentioned benefits are often balanced by its susceptibility to clutter [22,23], i.e., reflections coming from events that are unrelated to the target scattering characteristics but which occur in the same time window and have similar characteristics to the target wavelet. Being a deterministic signal, stable in time, might reduce the detection threshold of the system, resulting in an unacceptably high False Alarm Rate (FAR) [24].…”