We propose a magnetometer system fitted on an unmanned aerial vehicle (UAV, or drone) and a data-processing method for detecting metal antipersonnel landmines (M16) in the demilitarized zone (DMZ) in Korea, which is an undeveloped natural environment. The performance of the laser altimeter was improved so that the drone could fly at a low and stable altitude, even in a natural environment with dust and bushes, and a magnetometer was installed on a pendulum to minimize the effects of magnetic noise and vibration from the drone. At a flight altitude of 1 m, the criterion for M16 is 5 nT. Simple low-pass filtering eliminates magnetic swing noise due to pendulum motion, and the moving average method eliminates changes related to the heading of the magnetometer. Magnetic exploration was conducted in an actual mine-removal area near the DMZ in Korea, with nine magnetic anomalies of more than 5 nT detected and a variety of metallic substances found within a 1-m radius of each detection site. The proposed UAV-based landmine detection system is expected to reduce risk to detection personnel and shorten the landmine-detection period by providing accurate scientific information about the detection area prior to military landmine-detection efforts.

Many antipersonnel (AP) and antitank (AT) mines remain in the ground across South Korea; some are partially exposed and remain visible. We used a drone fit with a magnetometer to detect landmines. The magnetic characteristics of landmines were measured, and altitude and flight conditions (altitude <1 m) required for successful landmine detection were derived. Metallic AP and AT mines, and low metal content AT mines were detected in field tests under the proposed conditions. The drone can be used to aid in the demining of South Korea.

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.

This study presents an unmanned aerial vehicle (UAV)-borne vector magnetometer (MAG) system and proposes a new data-processing technique for modeling the residual magnetic anomalies of three types of landmines: the metallic antitank M15, the metallic antipersonnel M16, and the minimum-metal antitank M19. The burial depth and magnetic moment of these landmines were estimated using the measured and simulated residual magnetic anomalies based on the proposed UAV-borne vector MAG model. Initial in-flight validation showed a strong correlation between the residual magnetic anomaly maps obtained from measurements and simulations. To verify the detection capability in real-world conditions, the UAV-borne MAG system was tested at the Korean Combat Training Center. Both simulations and experiments demonstrated the effectiveness of the proposed data-processing method and UAV-borne MAG model in accurately modeling the residual magnetic anomalies of landmines with metallic components. This approach will facilitate the automated detection of M15, M16, and M19 landmines with high detection rates and enable accurate classification.

In this paper, a novel meander split power/ground plane is proposed for reducing crosstalk between parallel lines crossing over it. The working mechanism of the meander split scheme is investigated by simulations and measurements. The LC equivalent circuit and transmission line model are developed for modeling interactions between the meander split and the signal lines. The proposed meander structure enhances electromagnetic coupling between split planes. The capacitive coupling across the split ensures signal integrity and magnetic coupling between adjacent finger shaped structures suppresses lateral wave propagation along the split gap, which in turn helps suppress the crosstalk. The effectiveness of the meander split remains valid over very wide frequency ranges (up to 9 GHz). Experimental results show that the proposed structure improves the signal quality and reduces the near/far end crosstalk over 30 dB and 50% in the frequency domain and time domain, respectively.