Bistatic Landmine and IED Detection Combining Vehicle and Drone Mounted GPR Sensors

García-Fernández, María; Morgenthaler, Ann W.; Álvarez-López, Yuri; Las-Heras, Fernando; Rappaport, Carey M.

doi:10.3390/rs11192299

Cited by 26 publications

(15 citation statements)

References 11 publications

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“…With both transmitting and receiving antennas linearly polarized along the z-axis, we define the frequency response H zz (r rn , r tm , r q , ω) of a filter matched to a point scatterer with unit reflectivity at pixel r q , when the m-th antenna is transmitting and the n-th antenna is receiving, using (7) as…”

Section: Matched-filtering-based Near-field Tomographic Imagingmentioning

confidence: 99%

“…Microwave imaging has undergone significant advances in the last two decades, owing to its increased adoption and broad application in a variety of disciplines, including applied geophysics, planetary exploration, and emerging radar technologies [1][2][3][4][5][6][7]. Forward-looking ground penetrating radar (FL-GPR) is one such technology that employs microwave imaging for detection of targets buried at shallow depths in the ground.…”

Section: Introductionmentioning

confidence: 99%

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Coherence-Factor-Based Rough Surface Clutter Suppression for Forward-Looking GPR Imaging

et al. 2020

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We present an enhanced imaging procedure for suppression of the rough surface clutter arising in forward-looking ground-penetrating radar (FL-GPR) applications. The procedure is based on a matched filtering formulation of microwave tomographic imaging, and employs coherence factor (CF) for clutter suppression. After tomographic reconstruction, the CF is first applied to generate a “coherence map” of the region in front of the FL-GPR system illuminated by the transmitting antennas. A pixel-by-pixel multiplication of the tomographic image with the coherence map is then performed to generate the clutter-suppressed image. The effectiveness of the CF approach is demonstrated both qualitatively and quantitatively using electromagnetic modeled data of metallic and plastic shallow-buried targets.

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Section: Matched-filtering-based Near-field Tomographic Imagingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Coherence-Factor-Based Rough Surface Clutter Suppression for Forward-Looking GPR Imaging

et al. 2020

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“…In Reference [13], pedestrian movement detection using a small drone camera consists of frame subtraction, threshold, morphological filter, and false alarm reduction in consideration of the actual target size. In Reference [14], the paper has studied the Ground Penetrating Radar (GPR) system to detect land mines and Improvised Explosive Devices (IEDs) using vehicles and drones. The system consists of a transmitter mounted on a vehicle and a receiver mounted on a drone.…”

Section: Introductionmentioning

confidence: 99%

Improvement in Target Range Estimation and the Range Resolution Using Drone

Lee

2020

Electronics

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This study measured the speed of a moving vehicle in multiple lanes using a drone. The existing methods for measuring a vehicle’s speed while driving on the road measure the speed of moving automobiles by means of a sensor that is mounted on a structure. In another method, a person measures the speed of a vehicle at the edge of a road using a speed-measuring tool. The existing method for measuring a vehicle’s speed requires the installation of a gentry-structure; however, this produces a high risk for traffic accidents, which makes it impossible to measure a vehicle’s speed in multiple lanes at once. In this paper, a method that used a drone to measure the speed of moving vehicles in multiple lanes was proposed. The suggested method consisted of two LiDAR sets mounted on the drone, with each LiDAR sensor set measuring the speed of vehicles moving in one lane; that is, estimating the speed of moving vehicles in multiple lanes was possible by moving the drone over the road. The proposed method’s performance was compared with that of existing equipment in order to measure the speed of moving vehicles using the manufactured drone. The results of the experiment, in which the speed of moving vehicles was measured, showed that the Root Mean Square Error (RMSE) of the first lane and the second lane was 3.30 km/h and 2.27 km/h, respectively. The vehicle detection rate was 100% in the first lane. In the second lane, the vehicle detection rate was 94.12%, but the vehicle was not detected twice in the experiment. The average vehicle detection rate is 97.06%. Compared with the existing measurement system, the multi-lane moving vehicle speed measurement method that used the drone developed in this study reduced the risk of accidents, increased the convenience of movement, and measured the speed of vehicles moving in multiple lanes using a drone. In addition, it was more efficient than current measurement systems because it allowed an accurate measurement of speed in bad environmental conditions.

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“…when a wide aperture is needed for high azimuth resolution, or for squinted processing (useful to detect the steep internal ice layers). Through-The-Wall Imaging (TRWI) [4] and Ground Penetrating Radar (GPR) [5] techniques can address the refraction mechanisms with the small-angle approximation, although in some applications the effect of refraction is neglected under the straight-ray approximation [6]. In fields where the layering is needed, other approaches have been applied, such as using a look-up table [7] followed by an interpolation.…”

Section: Introductionmentioning

confidence: 99%

Efficient path estimation through parallel media for wide‐beam ice‐sounding radar

Arenas-Pingarrón

Brennan

Corr

2020

IET Radar, Sonar & Navigation

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We propose an algorithm to estimate the path followed by refracted signals from a source to a target, through a medium formed by uniform parallel layers with known different refractive indices, a common model used for ice radio-echo sounding. The analytical solution is a polynomial with a degree that exponentially depends on the number of layers, being computationally inefficient. For low incidence angles, the small-angle approximation can be used to avoid the polynomial. In our technique, we normalize the governing equations to obtain a framework where to find a narrow angular interval containing the solution, finally estimated interpolating the boundaries. The new approach improves the results regarding the small-angle approximation for a wider angular range at a slightly higher computational time. This method has been applied to focus airborne SAR images for deep ice sounding, reducing the calculation time and improving the detected response in wide-beam and squinted geometries, used for high along-track resolution or the detection of sloping internal layers.

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Bistatic Landmine and IED Detection Combining Vehicle and Drone Mounted GPR Sensors

Cited by 26 publications

References 11 publications

Coherence-Factor-Based Rough Surface Clutter Suppression for Forward-Looking GPR Imaging

Coherence-Factor-Based Rough Surface Clutter Suppression for Forward-Looking GPR Imaging

Improvement in Target Range Estimation and the Range Resolution Using Drone

Efficient path estimation through parallel media for wide‐beam ice‐sounding radar

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