Detection and Localization of Ferrous Underground Objects and Buried Utilities Using Airborne Magnetometers and Metal Detectors

Dobrovolskiy, Alexey

doi:10.3997/1365-2397.fb2021064

Cited by 2 publications

(2 citation statements)

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“…The ground reflection (𝑇 ) and landmine reflection (𝑇 ) exist about 25.62 ns and 26.66 ns, respectively. By utilizing the given information of the landmine burial depth (d = 3.5 cm) and propagation time (𝑇 − 𝑇 = 1.04 ns), we can estimate the relative permittivity and electromagnetic wave velocity of the ground using Equation (9), where 𝑐 and 𝑣 are the propagation velocities of waves in the air and ground, respectively. Furthermore, the B-scan raw data displays various indications of imperfections in the antenna impulse response, which can be attributed to ringdown or multiple reflections.…”

Section: Experimental Results Of the Uav-borne Gpr And Mag Modelmentioning

confidence: 99%

“…Unmanned aerial vehicles (UAVs) and drones have emerged as valuable tools in the field of landmine detection research. Recent studies have explored various detection strategies using lightweight sensors, such as ground penetrating radar (GPR) [1,2], ground penetrating synthetic aperture radar (GPSAR) [3][4][5][6], magnetometers (MAGs) [7,8], metal detectors [9,10], and thermal imaging cameras [11] mounted on UAVs for landmine detection. These techniques have numerous advantages, including precise autonomous flight capabilities; the potential for integrating multiple sensors, innovative avionic systems, and energy-efficient batteries; and substantially reduced costs and maintenance requirements.…”

Section: Introductionmentioning

confidence: 99%

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Modeling and Implementation of a Joint Airborne Ground Penetrating Radar and Magnetometer System for Landmine Detection

Lee,

et al. 2023

Remote Sensing

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We modeled and implemented a joint airborne system integrating ground penetrating radar (GPR) and magnetometer (MAG) models specifically for landmine detection applications. We conducted both simulations and experimental analyses of the joint airborne GPR and MAG models, with a focus on detecting the metallic components of different types of landmines, including antitank (AT) M15 metallic, antipersonnel (AP) M16 metallic, and AT M19 plastic (minimum-metal) landmines. The GPR model employed the finite-difference time-domain (FDTD) method and was evaluated using a singular value decomposition (SVD) and Kirchhoff migration (KM) with matched filtering (MF). These advanced techniques enabled the automatic identification and precise focusing of the reflected hyperbolic signals emitted by the landmines while considering cross-range resolution. Additionally, the MAGs were utilized based on the magnetic dipole model with a de-trend and a spatial median filtering method to estimate the magnetic anomaly of the landmines while considering various data spatial intervals. The joint airborne GPR and MAG system was implemented by combining and integrating the GPR and MAG models for experimental validation. Through this comprehensive approach, which included experiments, simulations, and data processing, the design parameters of the final system were obtained. These design parameters can be used in the development and application of landmine detection systems based on airborne GPR and MAG technology.

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Section: Experimental Results Of the Uav-borne Gpr And Mag Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling and Implementation of a Joint Airborne Ground Penetrating Radar and Magnetometer System for Landmine Detection

Lee,

et al. 2023

Remote Sensing

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Drone‐towed electromagnetic and magnetic systems for subsurface characterization and archaeological prospecting

Vilhelmsen,

Grayver,

Døssing

2024

Near Surface Geophysics

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Drone‐based geophysical surveying is an emerging measuring platform. High time‐cost efficiency and flexibility to survey over inaccessible areas make drones attractive or sometimes the only feasible option to carry geophysical measurements. This study presents a new drone‐towed electromagnetic induction and magnetic gradient sensor system used for near‐surface characterization and areal mapping.The system uses various datasets to enhance processing and interpretation. The system includes; an electromagnetic induction instrument; magnetic sensors; GNSS‐IMU system; photogrammetry; Lidar model data; and geoid model data. Robust data processing and stochastic inversion subsurface characterization for archaeological prospecting with drone‐towed electromagnetic induction and magnetic gradient sensor systems. Robust statistical methods were used to process the data.We conducted the fieldwork at one of the ancient Viking settlements in Denmark. The surveyed area was approximately 100200 m. We then implemented and applied a one‐dimensional laterally constrained non‐linear stochastic inversion to image the subsurface electrical conductivity. The inversion results show a consistent conductive layer at 5–8 m depths, likely associated with the groundwater level. This conductive layer is disrupted under a prominent anomaly within a 2–4 m wide area. Our analysis showed that this conductivity disruption could be a flint mine extending 7 m deep. This anomaly also has a strong signature in magnetic gradient data.

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Detection and Localization of Ferrous Underground Objects and Buried Utilities Using Airborne Magnetometers and Metal Detectors

Cited by 2 publications

References 0 publications

Modeling and Implementation of a Joint Airborne Ground Penetrating Radar and Magnetometer System for Landmine Detection

Modeling and Implementation of a Joint Airborne Ground Penetrating Radar and Magnetometer System for Landmine Detection

Drone‐towed electromagnetic and magnetic systems for subsurface characterization and archaeological prospecting

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