Anti-personnel Landmine Detection Research Articles

Development of a fully planar logarithmic spiral antenna with integrated balun in UWB GPR systems for landmines detection

ABSTRACT In this paper, a compact cavity-backed logarithmic spiral antenna with an integrated broadband planar balun is presented. This fully planar antenna is used for detection of anti-personnel (AP) landmines in GPR systems. Unlike conventional spiral antennas, which are fed by unbalanced coaxial cable or vertical baluns, and these feed lines make them bulky and frail, in this design, a microstrip-to-parallel strip balun is integrated with the spiral antenna and makes the whole structure compact, planar, and robust. Moreover, a metal cavity is utilized at the back of the antenna to prevent backward radiation and enhance the forward penetration depth to the ground. In choosing the operational frequency bandwidth, a compromise is made between the penetration depth and detection resolution. A prototype of the antenna is fabricated and its performance in landmine detection is evaluated with measurements. The measured results show that the antenna works over the frequency range of 1.5 GHz−4.5 GHz (bandwidth = 100%) with |S11| < −10 dB, a penetration depth of 10 cm in the soil with good detection resolution, gain >8 dB and axial ratio <3 dB. These factors make the proposed antenna a suitable candidate for pulse radar applications, in which low pulse distortion and wide bandwidth are key factors.

Antenna Design Considerations for Ground Penetrating Radar Landmine Detection

The performance of very short-range radar systems, such as ground penetrating radar for antipersonnel landmine detection, is critically dependent on the impulse characteristics of the antennas that are used. Typically, a pair of individual antennas is used in the radar, one for transmit and one for receive. These antennas are usually closely spaced for reasons of both portability and close in detectability. A variety of design techniques are used to achieve their wideband performance in terms of return loss, isolation, radiation patterns, polarization, and impulse formation. Not only the antenna elements but also their surrounds form the overall antenna structure and this ensemble becomes integral to the antenna performance and design process. Both the antenna and the surrounding structure can create late time signals or time sidelobes, which are in effect a form of self-generated clutter. Minimizing the duration of the antenna impulse response assists in reducing self-generated clutter and achieving optimum radar performance. This article considers the impact of the antenna on the system performance of the radar and shows that the clutter performance of the antenna can be the prime metric of system detection rather than the noise figure, given that the self-clutter often exceeds the latter.

Detection of antipersonnel landmines containing ANFO-based explosive: A review

After an internal conflict that lasted over half a century, the detection and removal of antipersonnel landmines in Colombia have become cumbersome challenges. Antipersonnel landmines remain scattered in Colombia and with a considerable impact on the central-western region. Most of these devices are handmade (therefore, they can also be classified as improvised explosive devices) and composed of ammonium nitrate and fossil fuel blend, a mixture known as ANFO. Due to several unique factors, including concealment tactics and non-conventional manufacturing techniques employed by guerrilla fighters, the most efficient method for the detection of ANFO-based antipersonnel landmines is the use of trained canines. This review aims at describing the current chemical strategies used in the detection of ANFO-based antipersonnel landmines. First, a detailed description of the different techniques used in the detection of explosives is made. Then, all the strategies reported in the world for antipersonnel landmines detection are described. Finally, the importance of the use of canines for antipersonnel landmines detection is explained.

Applying Deep Learning to Automate UAV-Based Detection of Scatterable Landmines

Recent advances in unmanned-aerial-vehicle- (UAV-) based remote sensing utilizing lightweight multispectral and thermal infrared sensors allow for rapid wide-area landmine contamination detection and mapping surveys. We present results of a study focused on developing and testing an automated technique of remote landmine detection and identification of scatterable antipersonnel landmines in wide-area surveys. Our methodology is calibrated for the detection of scatterable plastic landmines which utilize a liquid explosive encapsulated in a polyethylene or plastic body in their design. We base our findings on analysis of multispectral and thermal datasets collected by an automated UAV-survey system featuring scattered PFM-1-type landmines as test objects and present results of an effort to automate landmine detection, relying on supervised learning algorithms using a Faster Regional-Convolutional Neural Network (Faster R-CNN). The RGB visible light Faster R-CNN demo yielded a 99.3% testing accuracy for a partially withheld testing set and 71.5% testing accuracy for a completely withheld testing set. Across multiple test environments, using centimeter scale accurate georeferenced datasets paired with Faster R-CNN, allowed for accurate automated detection of test PFM-1 landmines. This method can be calibrated to other types of scatterable antipersonnel mines in future trials to aid humanitarian demining initiatives. With millions of remnant PFM-1 and similar scatterable plastic mines across post-conflict regions and considerable stockpiles of these landmines posing long-term humanitarian and economic threats to impacted communities, our methodology could considerably aid in efforts to demine impacted regions.

Combining Electromagnetic Spectroscopy and Ground-Penetrating Radar for the Detection of Anti-Personnel Landmines.

Dual mode detectors combining metal detection and ground-penetrating radar are increasingly being used during humanitarian demining operations because of their ability to discriminate metal clutter. There are many reports in the academic literature studying metal detector and ground-penetrating radar systems individually. However, the combination of these techniques has received much less attention. This paper describes the development of a novel dual modality landmine detector, which integrates spectroscopic metal detection with ground-penetrating radar. This paper presents a feature-level sensor fusion strategy based on three features extracted from the two sensors. This paper shows how the data from the two components can be fused together to enrich the feedback to the operator. The algorithms presented in this paper are targeted at automating the location of buried, visibly obscured objects; however, the system described is also capable of collecting information which could also be used for the potential classification of such items.

Robust landmine detection from thermal image time series using Hough transform and rotationally invariant features

ABSTRACT Automated detection of buried anti-personnel landmines using remote sensing techniques is very important for clearing minefields without putting lives in danger. Although thermal infrared imaging is promising, it is far from applicable to the real world in its current state-of-the-art. The most serious problem is that experiments are generally held using sandboxes or levelled and cleared soil, but real fields are, at least partially, covered with plants. In this study, we present an algorithm for landmine detection that is robust enough to detect beyond the clutter caused by partial plant cover. The first part is a hypothesis generator based on circular Hough Transform applied to images that are filtered to enhance circular structures. The second part tests the candidate landmine coordinates using rotationally invariant features, including modified Histogram of Oriented Gaussians (HOG), over multiple images taken at different times after Wiener filtering to maximize signal-to-clutter ratio. The performances of various features and classifiers are compared. The overall performance of the algorithm is demonstrated on a dataset of real-world landmine images contaminated by simulated plants. Satisfactory results are obtained up to 40% equivalent plant coverage where more than 65% of the pixels are fully or partially covered by plants.

Development of a logarithmic spiral antenna in UWB GPR for humanitarian demining

ABSTRACTA low cost cavity-backed logarithmic spiral antenna with a very wideband balun is presented for detection of Anti-Personnel land mines in ground penetrating radars. It covers a wide frequency range of 0.5 to 1.6 GHz with 10 dB return loss. The measured maximum gain of the antenna at the center frequency of 1.0 GHz, is 9.2 dBi and the axial ratio is less than 1.3 dB in the angular range of ±48°, which validates circular polarization performance. The fabricated antenna is useful in impulse GPRs for humanitarian demining due to its high penetration depth, wide bandwidth, relatively small dimensions, and low axial ratio.

Development of Autonomous Self-Powered Robotic System for Antipersonnel Landmines Detection and Extraction

Detection and removal of antipersonnel landmines has become one of major scientific and technological challenges. Conventional methods of demining are expensive, slow and low efficiency. There is a dire need for automated, efficient, lowcost, and self powered robotic systems for the purpose of mine detection and disposal. This paper deals with the design and development of a novel low cost robotic system for mine detection and extraction. This robotic system consists of a mobile platform carrying flexible arm, the sensors system and the developed electronic cards of the system. The sensors system comprises an efficient design of metal detector sensor in addition to a distributed sensors fusion system that identifies the robot environment and operation. The robot extracts the mine by drilling the soil around the mine without touching it, catching the mine and extracting it from the ground while enabling the operator to control the robot wirelessly from a safe distance. A renewable solar power supply is supplemented to provide the system with the necessary power. Control of the overall system is achieved using PICs 18F452 microcontroller circuits. A prototype is developed and extensive field tests were performed that confirms the success of the illustrated design.

Energy-efficiency hexapod walking robot for humanitarian demining

PurposeThe aim of this paper is to introduce a hexapod walking robot specifically designed for applications in humanitarian demining, intended to operate autonomously for several hours. To this end, the paper presents an experimental study for the evaluation of its energy efficiency.Design/methodology/approachFirst, the interest of using a walking robot for detection and localization of anti-personnel landmines is described, followed by the description of the mechanical system and the control architecture of the hexapod robot. Second, the energy efficiency of the hexapod robot is assessed to demonstrate its autonomy for performing humanitarian demining tasks. To achieve this, the power consumed by the robot is measured and logged, with a number of different payloads placed on-board (always including the scanning manipulator arm assembled on the robot front end), during the execution of a discontinuous gait on flat terrain.FindingsThe hexapod walking robot has demonstrated low energy consumption when it is carrying out several locomotion cycles with different loads on it, which is fundamental to have a desired autonomy. It should be considered that the robot has a mass of about 250 kg and that it has been loaded with additional masses of up to 170 kg during the experiments, with a consumption of mean power of 72 W, approximately.Originality/valueThis work provides insight on the use of a walking robot for humanitarian demining tasks, which has high stability and an autonomy of about 3 hours for a robot with high mass and high payload. In addition, the robot can be supervised and controlled remotely, which is an added value when it is working in the field.

Multi-parameter optimization of a (3He-252Cf-3He) neutron backscattering sensor for landmine detection

Experimental measurements were carried out to optimize the performance of a (3He-252Cf-3He) assembly for plastic anti-personnel landmine detection in dry soils. This is done by employing a 252Cf source producing 0.7 × 104 n.s−1 and a pair of two identical 3He detectors. The Signal-to-background ratio due to the responses of the two 3He detectors is monitored and analyzed as a function of detector-detector distance, stand-off distance, mine depth and source position while scanning the mine. The laboratory measurements were followed by Monte Carlo simulations to explore the capabilities of the laboratory measurements in the presence of 252Cf sources producing 104n.s−1 and 106n.s−1. The optimal 252Cf source was selected and employed in further Monte Carlo simulations to study the impact of a multi-layer shield on the performance of the (3He-252Cf-3He) assembly.

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.

Numerical evaluation of a landmine detection system based on the neutron back scattering technique

This paper describes an anti-personnel landmine detection system, which is based on the neutron back-scattering technique. It consists of a point-like isotopic neutron source (252Cf, 2,31 × 107 n/s), eight BF3 detectors and a neutron moderating and shielding block made from borated paraffin (3 wt%). It was modeled and tested by carrying out Monte Carlo calculations (MCNP-4C2 Code). The tests were performed in some troublesome conditions which include long burial depths for a landmine, higher humidity levels in the formation and existence of some plastics-like substances in the scanning area near a mine. Use of the neutron moderator behind the BF3 detectors increased the counting statistics and improved the S/N ratio. The system could detect a small cylindrical land mine (<300 g) until a burial depth of 15 cm in limestone and also worked well in distinguishing trinitrotoluene (TNT) from the other nearby substances. However, the presence of moisture in limestone in the level of 5% limited its applicability. Scanning speed of the system was calculated as 9.6 m2/min on an even land surface. The calculations revealed that it would be worthwhile to construct and test such a simple and fast practical system for detecting nonmetallic land mines in a laboratory environment. Key words: Neutron backscattering, landmine, BF3 detectors, 252Cf, MCNP.

Proton transfer reaction mass spectrometry for the sensitive and rapid real-time detection of solid high explosives in air and water

Relying on recent developments in proton transfer reaction mass spectrometry (PTR-MS), we demonstrate here the capability of detecting solid explosives in air and in water in real time. Two different proton transfer reaction mass spectrometers have been used in this study. One is the PTR-TOF 8000, which has an enhanced mass resolution (m/Δm up to 8,000) and high sensitivity (~50 cps/ppbv). The second is the high-sensitivity PTR-MS, which has an improved limit of detection of about several hundreds of parts per quadrillion by volume and is coupled with a direct aqueous injection device. These instruments have been successfully used to identify and monitor the solid explosive 2,4,6-trinitrotoluene (TNT) by analysing on the one hand the headspace above small quantities of samples at room temperature and from trace quantities not visible to the naked eye placed on surfaces (also demonstrating the usefulness of a simple pre-concentration and thermal desorption technique) and by analysing on the other hand trace compounds in water down to a level of about 100 pptw. The ability to identify even minute amounts of threat compounds, such as explosives, particularly within a complex chemical environment, is vital to the fight against crime and terrorism and is of paramount importance for the appraisal of the fate and harmful effects of TNT at marine ammunition dumping sites and the detection of buried antipersonnel and antitank landmines.

Studies on the properties of an epithermal-neutron hydrogen analyzer

Systematic investigations have proved the advantages of the Epithermal Neutron Analyzer (ETNA) for bulk hydrogen analysis as compared to the thermal neutron techniques. Results can contribute, for example, to the design and construction of instruments needed for the detection and identification of plastic anti-personnel landmines, explosives hidden in airline baggage and cargo containers via hydrogen contents as an indicator of their presence.

Advances in GPR-based landmine automatic detection

Abstract As an application of mechatronics, this paper presents the advances in surface-adaptive ground penetrating radar (GPR)-based anti-personnel landmine detection project in Nagoya University. These advances can be summarized in three items: (1) GPR manipulation where a low-pressure-tire vehicle capable of moving inside a mine field, to facilitate machine-based sensing in place of manual sensing, is applied; (2) enhancement of underground landmine suspects’ images through geography adaptive scanning and measurements signal processing of a vector frequency modulated continuous wave (FMCW) GPR; (3) GPR fusion with metal detector (MD) for automatic decision making through experimental-based fuzzy learnt fusion rules. The state-of-art of these advances as well as directions for future research work is to be presented.

Improving the moderator geometry of an anti-personnel landmine detection system

The optimum moderating geometry using an 241Am–Be neutron source for detecting landmines has been investigated. The experimental setup composed of a Pb cylindrical shell enclosing the neutron source, embedded in a fixed-size high-density polyethylene cylinder with a variable thickness of the upper and lower moderator/reflector. According to the fact that the increased flux of thermal neutrons in the mine position yields increased prompt gamma rays, some groups of experiment have been done to measure several moderator configurations’ responses, replacing a thermal neutron detector with the landmine and counting the neutron capture events.

Fuzzy Sensor Fusion for Humanitarian Demining

In this paper, an automatic sensor-fusion based detection algorithm of an anti-personnel land mine is presented. A “feature in-decision out” fuzzy sensor fusion algorithm for a ground penetrating radar (GPR), and a metal detector (MD), for anti-personnel landmine detection is introduced. The inputs to the fuzzy fusion system are features extracted from both GPR and MD measurements. The output from the fuzzy fusion system is a decision if there is a land mine and at what depth it would be. Fuzzy fusion rules are extracted from training data through a fuzzy learning algorithm. Experimental test results are presented to demonstrate the validity of the proposed fuzzy fusion algorithm and hence its influence in minimizing the false alarm rate for humanitarian demining.

Comparative studies of the globally convergent convexification algorithm with application to imaging of antipersonnel land mines

A comparative study of various aspects on the globally convergent convexification algorithm for coefficient inverse problems is described. Numerical results of the algorithm with application to detection of antipersonnel land mines are presented. The aspects studied include initial guess and layer size for the layer stripping approach, dimensions of the basis for spatial and pseudo-frequency approximations, the lower limit of the integrals with respect to pseudo-frequency κ, the stopping criteria of steepest descent method in the least squares minimization, the tails to compensate the truncated integration with respect to κ, the parameter λ associated with the Carleman weight function, and adding different noise levels to the input data for the coefficient inverse problems. With our new implementation, the convexification algorithm is very efficient and feasible to be applied in real time to detect antipersonnel land mines in the field.

Prediction of the effects of soil and target properties on the antipersonnel landmine detection performance of ground-penetrating radar: A Colombian case study

The performance of ground-penetrating (GPR) radar is determined fundamentally by the soil electromagnetic (EM) properties and the target characteristics. In this paper, we predict the effects of such properties on the antipersonnel (AP) landmine detection performance of GPR in a Colombian scenario. Firstly, we use available soil geophysical information in existing pedotransfer models to calculate soil EM properties. The latter are included in a two-dimensional (2D), finite-difference time-domain (FDTD) modeling program in conjunction with the characteristics of AP landmines to calculate the buried target reflection. The approach is applied to two soils selected among Colombian mine-affected areas, and several local improvised explosive devices (IEDs) and AP landmines are modeled as targets. The signatures from such targets buried in the selected soils are predicted, considering different conditions. Finally, we show how the GPR can contribute in detecting low- and non-metallic targets in these Colombian soils. Such a system could be quite adequate for complementing humanitarian landmine detection by metal detectors.

Filtering Soil Surface and Antenna Effects From GPR Data to Enhance Landmine Detection

The detection of antipersonnel landmines using ground-penetrating radar (GPR) is particularly hindered by the predominant soil surface and antenna reflections. In this paper, we propose a novel approach to filter out these effects from 2-D off-ground monostatic GPR data by adapting and combining the radar antenna subsurface model of Lambot with phase-shift migration. First, the antenna multiple reflections originating from the antenna itself and from the interaction between the antenna and the ground are removed using linear transfer functions. Second, a simulated Green's function accounting for the surface reflection is subtracted. The Green's function is derived from the estimated soil surface dielectric permittivity using full-wave inversion of the radar signal for a measurement taken in a local landmine-free area. Third, off-ground phase-shift migration is performed on the 2-D data to filter the effect of the antenna radiation pattern. We validate the approach in laboratory conditions for four differently detectable landmines embedded in a sandy soil. Compared to traditional background subtraction, this new filtering method permits a better differentiation of the landmine and estimation of its depth and geometrical properties. This is particularly beneficial for the detection of landmines in low-contrast conditions