Landmine Detection Method Research Articles

Unmanned aerial vehicle for magnetic detection of metallic landmines in military applications

Landmines significantly hinder the rapid movement of military forces and pose major obstacles during critical operations. Unmanned aerial vehicles (UAVs), commonly known as drones, offer several significant advantages for landmine detection. Most studies have tested drone-based systems at controlled sites and demonstrated their effectiveness in limited scenarios, with no examples of using these systems to detect landmines and relay the results to mine clearance machines (MCMs) for actual removal in real military operations. This study evaluated the use of UAVs equipped with magnetometers to detect metallic landmines in military applications. By conducting a series of controlled experiments, the research identified optimal flight conditions—2 m/s flight speed, 1 m survey interval, and 0.5 m sensor altitude—that balance accuracy and operational efficiency. The findings demonstrate that UAV-based magnetometer systems can significantly enhance mine clearance operations by providing near real-time data to MCMs. This approach offers a safer, faster, and more cost-effective alternative to traditional landmine detection methods by addressing the limitations of ground-based operations, such as high risk to human operators and inefficiency.

Review of strategies to overcome the lack of data in landmine detection

This article reviews strategies to address the lack of data for training landmine recognition models. Since the outbreak of the war in Ukraine in 2014, the area of contaminated territories has gradually increased. However, after Russia's full-scale invasion on February 24, 2022, the problem of landmines in Ukraine has become much more severe, as the area of mined territories in the country has increased to 30%. It takes many years and efforts to clear such a large area. To overcome a problem of this scale, it is necessary to look for new methods of landmine detection that will allow demining to be conducted 24/7. Machine learning is one of the options for solving the problem of landmine detection. To train landmine recognition models, a large amount of data is required. However, the lack of diverse and large datasets creates significant obstacles to the development of effective detection systems. The safety concerns associated with conducting experiments with real landmines further exacerbate the problem. This article discusses three possible strategies to overcome the above problem: augmentation methods, the use of 3D printing technology, and crowdsourced data collection. Augmentation methods offer data generation to improve model performance. 3D printing allows for the creation of realistic replicas of landmines for safe experimentation. Crowdsourcing uses collective efforts to collect real-world data from conflict zones. Through the joint efforts of researchers, technology developers and humanitarian organizations, these approaches offer promising ways to improve landmine detection capabilities. The use of these approaches can address the data gap and ensure safe data collection.

A novel landmine detection system based on within and between subclasses dispersion information

ABSTRACT : Millions of anti-personnel landmines have been left in the ground during war conflicts in many countries, which causes many security, humanitarian and economic problems. It is therefore necessary to develop an automatic and efficient technique for landmines detection and localization, in order to clear the existing minefields. Ground-penetrating radar (GPR) is a geophysical method that is able to detect any buried object in the soil, but it suffers from high false alarm rate. Several landmine detection and localization systems have been developed, using GPR data and based on competitive classification methods, such as the One-class Support Vector Machine (OSVM), which handles the common problem of unbalanced data, in a proper manner. Nevertheless, in the landmine detection problem, we assume that the target class is composed of several subclasses related to metallic contents, which are not considered by related classification methods, including OSVM. For this reason, in this paper, we propose a subclass landmine detection and localization system based on a novel variation of the OSVM that takes into account the existence of subclasses in the landmine target class in order to jointly minimize the within and between subclass dispersion and to estimate the optimal decision function. Our proposed landmine detection and localization method has been evaluated and compared to other methods based on relevant one-class classifiers, on several real-world datasets extracted from the well-known MACADAM database. Experimental results have shown clearly that our proposed method is competitive with the existing relevant one-class classifiers, in landmine detection.

Honeybee-based biohybrid system for landmine detection

Legacy landmines in post-conflict areas are a non-discriminatory lethal hazard and can still be triggered decades after the conflict has ended. Efforts to detect these explosive devices are expensive, time-consuming, and dangerous to humans and animals involved. While methods such as metal detectors and sniffer dogs have successfully been used in humanitarian demining, more tools are required for both site surveying and accurate mine detection. Honeybees have emerged in recent years as efficient bioaccumulation and biomonitoring animals. The system reported here uses two complementary landmine detection methods: passive sampling and active search. Passive sampling aims to confirm the presence of explosive materials in a mine-suspected area by the analysis of explosive material brought back to the colony on honeybee bodies returning from foraging trips. Analysis is performed by light-emitting chemical sensors detecting explosives thermally desorbed from a preconcentrator strip. The active search is intended to be able to pinpoint the place where individual landmines are most likely to be present. Used together, both methods are anticipated to be useful in an end-to-end process for area surveying, suspected hazardous area reduction, and post-clearing internal and external quality control in humanitarian demining.

Simulation of PGNAA Landmine Detection Method by MOCA Program

Simulation of PGNAA Landmine Detection Method by MOCA Program

Landmine detection training simulation using virtual reality technology

Landmines are frequently used for defence and attack. Thus, landmine detection is vital to preventing the damages incurred. Various landmine detection methods have been developed from the past to the present. Thus, a need has arisen for the employment of qualified personnel in this field. In today’s landmine detection training, soldiers are first subjected to theoretical training about landmine types. After this stage, they attend practical training in the field. However, when training is given in this way, sample application fields do not contain all possible terrain and weather conditions. Also, many accidents and injuries occur during this practical training. To overcome the disadvantages elucidated above, a landmine detection training simulation was developed in this study, which supports real terrain conditions and creates a safe detection environment. In this study, the developed simulation software was based on virtual reality technology. The interaction with the computer is both provided by a detector appearance control device (DACD) controller developed for this simulator and by Kinect controller. The simulator has remarkable benefits concerning time and cost when compared with the landmine detection training given today. At the same time, detections performed in a safe environment without any risk factors and real land conditions were provided close to reality. Also, the actual space coordinates of the joints in the human body can be detected correctly using the DACD controller, as much as the Kinect device.

Combination of physics-based and image-based features for landmine identification in ground penetrating radar data

Ground penetrating radar (GPR) is a powerful technology for detection and identification of buried explosives, especially with little or no metal content. However, subsurface clutter and soil distortions increase false alarm rates of current GPR-based landmine detection and identification methods. Most existing algorithms use shape-based, image-based, and physics-based techniques. Analysis of these techniques indicates that each type of algorithm has a different perspective to solve the landmine detection and identification problem. Therefore, one type of method has stronger and weaker points with respect to the other types of algorithms. To reduce false alarm rates of the current GPR-based landmine detection and identification methods, we propose a combined feature utilizing both physics-based and image-based techniques. Combined features are classified with a support vector machine classifier. The proposed algorithm is tested on a simulated data set that contained more than 500 innocuous object signatures and 400 landmine signatures, over half of which are completely nonmetal. The results presented indicate that the proposed method has significant performance benefits for landmine detection and identification in GPR data.

Magnetic and infrared thermography methods in detection of antipersonnel landmines

Purpose – The purpose of this paper is to present two methods of detection for landmines with minimal metal content. Design/methodology/approach – First, two methods of landmine detection are presented: magnetic and infrared with microwave heating. For each method the numerical algorithm of an object’s position and properties determination are presented. Furthermore, the experimental results of several landmines detection using both methods are presented. Findings – It is possible to detect the landmines with minimal metal content using both magnetic and infrared methods. It is also possible to determine the detected objects’ exact position and properties using developed numerical algorithms. Originality/value – The idea of using the magnetic method to detect the plastic landmines is, to the best knowledge of the authors, new. For both methods, the numerical algorithms of objects’ parameters determination are original.

Measurement and modeling of pulsed bi-frequency, nonlinear acoustic excitation of buried landmines

To help resolve certain practical issues with acoustical methods for humanitarian landmine detection, we have researched using a pulsed, standoff source method for acoustical excitation of the buried mine [J. Acoust. Soc. Am. 130, 2541 (2011); J. Acoust. Soc. Am. 133, 3457 (2013)]. Pulses consisting of two primary frequencies are used in order to search for induced nonlinear vibrations at interaction frequencies such as the sum frequency, which arise due to nonlinear interaction at the mine/soil interface. To model the pulsed excitation, we employ a fully nonlinear time-domain implementation of the lumped-element model of nonlinear soil/mine interaction introduced by Donskoy et al. [J. Acoust. Soc. Am. 117, 690 (2005)]. Modeling is compared with experimental results, which are obtained with bi-frequency pulses exciting a soil with a buried landmine replica, instrumented with a geophone and a nearby microphone. Cases investigated include: (1) target only, (2) buried target under disturbed soil, (3) disturbed soil only, and (4) undisturbed soil. Excitation both on and off the resonance of the buried mine is also investigated, as is burial in different soil types at various depths. [Work supported by the ARL:UT McKinney Fellowship in Acoustics.]

Research on High-Pressure Water Jet Target Object Detection Parameter Optimization

By using the unique characteristics of high pressure water jet, sound test, analysis and recognition techniques combined with high pressure water jet, collecting target reflected sound signal characteristic value, then by the analysis processing, to achieve recognition for classification purposes, can form a kind of brand-new landmine detection method. For the ultimate realization of the target of effective detection and classification, it must be determined on the reflected sound signal of water jet hydraulic parameters and reasonable choice of the walking device and a signal acquisition device parameters. Effects on reflected sound signal characteristic value quality parameters include: nozzle diameter, jet pressure, nozzle and the target of target distance, jet angle and jet scanning speed. By parameter optimization, the system can complete identification of material and geometry of eigenvalue.

A novel detection and navigation approach based on OWA fusion method

PurposeThe purpose of this paper is to design and implement a landmine detection robot (Venus) equipped with three electromagnetic sensors and controlled by ordered weighted averaging (OWA) sensor fusion approach. Higher numbers of detected mines in a fixed time interval and lower total power consumption are the achieved goals of this research.Design/methodology/approachOWA sensor fusion is exploited for data combination in this paper. Unlike most other landmine detection robots, Venus has three electromagnetic sensors, the positions of which can be adjusted according to the environmental conditions. Also, a novel approach for OWA weight dedication using Gaussian distribution function is applied and the whole idea is evaluated practically in several randomly mined fields. Finally, for better evaluation, performance of Venus is compared with the other two landmine detection robots.FindingsThe simulation and experimental results proved that in a predetermined interval of time, not only total energy consumption is reduced, but also by expanding the surface and the depth of influence of electromagnetic waves, the number of detected mines is considerably raised.Social implicationsIn contrast to the regular demining process, which is relatively expensive and complicated, the landmine detection method proposed in this research is surprisingly simple, cost effective, and efficient. Therefore, it may be attractive for every company or organization in this field of research.Originality/valueThe paper describes research which implements and evaluates a novel control approach based on OWA sensor fusion method, a new way of using Gaussian distribution function for determining OWA weights, and also an adaptive physical configuration for sensors based on environmental conditions.

Landmine detection method combined with backscattering neutrons and capture γ-rays from hydrogen

The usefulness of the measurements of the backscattering neutron and 2.22MeV capture γ-ray from hydrogen in the landmine detection method is described in this paper. When the soil moisture content is increased, the reaction rates of both the neutron scattering reaction and capture reaction are increased. However, the backscattering neutrons are more influenced than the capture γ-rays by the soil moisture before the reaction with the detector. The facts that the backscattering neutron method is useful in the dry soil case and that the capture γ-ray method is effective in well-wet soil case are confirmed by the experiments and the calculations. The landmine detection efficiency is improved in various soil moisture conditions by combining the backscattering neutron method together with the capture γ-ray method. The effectiveness of the pulse mode operation was confirmed numerically.

트리즈의 6단계 창의성을 이용한 지뢰탐지 판별에 관한 연구

지뢰는 민간인을 무차별적으로 죽이고 불구로 만들기 때문에 인도주의에 이의를 제기한다. 지뢰는 군인과 민간인을 구별하지 않고, 수십년동안 작동하는 무기이다. 그 결과, 대부분 지뢰 희생자는 아무 죄가 없는 남녀노소이다. 이러한 목적으로 새로운 기술의 지뢰탐지 방법과 이동로봇이 필요한다. 우리의 연구는 지뢰탐지를 위한 소형 이동로봇을 개발하는 것과 지뢰 탐지, 탐지된 지뢰를 구분하는 것이다. 이 논문에서 전자기 센서를 사용하여 지뢰를 탐지했고, TRIZ의 6단계 창의성을 이용하여 탐지된 물체가 금속인지 M14 비금속 지뢰인지를 명확하게 판별하였으며, TRIZ를 이용한 새로운 지뢰 탐지 및 판별 방법을 제안하였다. Landmines are a humanitarian challenge because they indiscriminately kill and maim civilians. Landmines are weapons that cannot distinguish between a soldier and a civilian, and they remain active for decades. As a result, most of the victims of mines are innocent men, women and children. For this purpose, new technologies such as a methode of landmine detection and mobile robots are needed. Our effort is to develop a small mobile robot for landmine detection, to detect landmine and to explore the landmine distinguishable method. In this paper, Specifically we detected landmines using electromagnetic sensors and distinguished metals from M14 antipersonnel mines under the ground using 6 step creativity of the TRIZ. Therefore, we proposed new method of landmine detection using the TRIZ.

Tunable Generation and Adsorption of Energetic Compounds in the Vapor Phase at Trace Levels: A Tool for Testing and Developing Sensitive and Selective Substrates for Explosive Detection

Among various methods for landmine detection, as well as soil and water pollution monitoring, the detection of explosive compounds in air is becoming an important and inevitable challenge for homeland security applications, due to the threatening increase in terrorist explosive bombs used against civil populations. However, in the last case, there is a crucial need for the detection of vapor phase traces or subtraces (in the ppt range or even lower). A novel and innovative generator for explosive trace vapors was designed and developed. It allowed the generation of theoretical concentrations as low as 0.24 ppq for hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in air according to Clapeyron equations. The accurate generation of explosive concentrations at subppt levels was verified for RDX and 2,4,6-trinitrotoluene (TNT) using a gas chromatograph coupled to an electron capture detector (GC-ECD). First, sensing material experiments were conducted on a nanostructured tungsten oxide. The sensing efficiency of this material determined as its adsorption capacity toward 54 ppb RDX was calculated to be five times higher than the sensing efficiency of a 54 ppb TNT vapor. The material sensing efficiency showed no dependence on the mass of material used. The results showed that the device allowed the calibration and discrimination between materials for highly sensitive and accurate sensing detection in air of low vapor pressure explosives such as TNT or RDX at subppb levels. The designed device and method showed promising features for nanosensing applications in the field of ultratrace explosive detection. The current perspectives are to decrease the testing scale and the detection levels to ppt or subppt concentration of explosives in air.

DETERMINATION OF NEUTRON DETECTORS SHIELD USED FOR THE DETECTION OF LANDMINES

As a result of being hydrogenous moderators, several landmine detection methods based onnuclear techniques have been suggested in recent years. Because of elastic scattering and moderating neutrons from hydrogen atoms in landmines, detection of backscattered neutron shows an anomaly in the reflected thermal neutrons count when a detector scans over a mine. On landmine detection using neutron sources, a detector and its shielding play an important role. In this paper, based on the investigations and calculations performed by MCNP code (Monte Carlo N-Particle transport code), detector shielding materials and their thicknesses have been determined. Therefore, the effects of moderators such as graphite, heavy water, beryllium, polyethylene and boric acid on backscattered neutron flux have been investigated.

Varied amplitude method in time reversal acoustic land mine

Acoustic methods of land mine detection are being developed for nonmetal mines where conventional electromagnetic methods fail. One such method, based on time reversal acoustic principles, is the hhase-inversion method; which detects quadratic and even ordered harmonic nonlinearities in the surface vibration above a mine. While this has shown higher sensitivity than linear methods it cannot detect all nonlinear components. These components can be detected by the Varied Amplitude method that is based on wide band excitation of surface vibration using the principles of time reversal acoustics. The nonlinear effects are measured for surface vibrations with different amplitudes and the normalized received signals can then be subtracted to reveal all the nonlinear components. We conducted a set of experiments using a box with six loudspeaker and an array of spatially distributed geophones to measure the linear and nonlinear components for various types of mines in different soils. Information about nonlinear components' spatial distribution allows one to observe greater mine/no mine contrast than with linear and other nonlinear techniques. [Work was supported by the U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate.]

Mechanical resonances in the low‐frequency vibration spectrum of a cylindrically symmetric, anti‐tank landmine

Acoustic‐based landmine detection methods have enjoyed success, in part, because of structural resonances in many landmines. The unburied VS 1.6, a member of a family of plastic, cylindrically symmetric anti‐tank landmines, exhibits seven modes below 1.6 kHz and a large frequency shift of the first symmetric mode such that its frequency is greater than that of the first asymmetric mode, a phenomenon observed in timpani of reduced kettle volume [Christian et al., J. Acoust. Soc. Am., 76(5), 1336‐1345 (1984)]. An elastically supported, thin, elastic plate acceptably models the unperturbed modes of the pressure plate. Coupling of the acoustic analog of the first symmetric mode to the cavities beneath the plate shows those cavities to be the cause of the perturbation. Shallow burial in sand effectively removes the frequency shift of the first symmetric mode. Comparisons to burial simulation experiments in water will be made, thus allowing a qualitative explanation of the effect sand has on the first symmetric mode of the plate. [This work was sponsored by US Army Research, Development, and Engineering Command, Night Vision and Electronic Sensors Directorate under Contract DAAB15‐02‐C‐0024.]

Fast acoustic landmine detection using multiple beam laser Doppler vibrometry

An acoustic method of buried landmine detection consisting of excitation of the ground using airborne sound or seismic waves in the frequency range from about 50 Hz to 1000 Hz, and obtaining a velocity image of the ground surface with a laser Doppler vibrometer (LDV) has been developed and successfully tested in the laboratory and field experiments. The presence of a buried landmine can be detected by an abnormality in the velocity image. Initially, the scanning single‐beam LDV created a velocity image of the ground through point‐by‐point measurements, which resulted in a long measurement time. To reduce this measurement time, a multiple beam LDV having 16 beams configured in a linear array was developed and successfully used in field experiments. To further reduce the time of measurement, a full‐field LDV capable of making 256 vibration measurements in parallel on the target, configured as 16x16 square array of points equally separated in x‐ and y‐directions has been recently developed. The system is capable of creating a two‐dimensional vibrational velocity image of the ground surface in the time defined by the required frequency resolution. The parallel measurement makes the system a unique tool to measure transient vibrations.

Nonlinear time reversal acoustic method of land mine detection: Experiment and modeling

The nonlinear vibration response of land mines is an effective detection clue. This response can be measured by application of two frequency acoustic waves producing a vibration spectrum above the mine that is different from its surrounding. As an alternative to this approach, this work investigates time reversal techniques as a method of acoustically exciting nonlinear mine vibrations over a broad frequency range. The phase-inversion method used here requires two short broadband time-reversed focused signals with opposite sign, i.e. phase inverted. The focused signal and the inverted focused signal are broadcast sequentially and the responses are summed in post processing. This cancels the linear response leaving the nonlinear component. A theoretical model has been developed that treats the mine stiffness as a nonlinear spring. It predicts that the dominant nonlinear frequencies correspond to the second harmonics of the mine’s primary resonance. Experiments were conducted using six loudspeakers in a box placed directly over a mine. The measured responses confirm most of the model predictions, and illustrate differences between the soil and mine nonlinearities. Work was supported by the U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate

Granular layers on vibrating plates: Effective bending stiffness and particle-size effects

Acoustic methods of land mine detection rely on the vibrations of the top plate of the mine in response to sound. For granular soil (e.g., sand), the particle size is expected to influence the mine response. This hypothesis is studied experimentally using a plate loaded with dry sand of various sizes from hundreds of microns to a few millimeters. For low values of sand mass, the plate resonance decreases with added mass and eventually reaches a minimum without particle size dependence. After the minimum, a frequency increase is observed with additional mass that includes a particle-size effect. Analytical nondissipative continuum models for granular media capture the observed particle-size dependence qualitatively but not quantitatively. In addition, a continuum-based finite element model (FEM) of a two-layer plate is used, with the sand layer replaced by an equivalent elastic layer for evaluation of the effective properties of the layer. Given a thickness of sand layer and corresponding experimental resonance, an inverse FEM problem is solved iteratively to give the effective Young's modulus and bending stiffness that matches the experimental frequency. It is shown that a continuum elastic model must employ a thickness-dependent elastic modulus in order to match experimental values.