Buried Landmines Research Articles

Synthetic Aperture Radar Imaging Below a Random Rough Surface

AbstractMotivated by applications in unmanned aerial based ground penetrating radar for detecting buried landmines, we consider the problem of imaging small point like scatterers situated in a lossy medium below a random rough surface. Both the random rough surface and the absorption in the lossy medium significantly impede the target detection and imaging process. Using principal component analysis we effectively remove the reflection from the air‐soil interface. We then use a modification of the classical synthetic aperture radar imaging functional to image the targets. This imaging method introduces a user‐defined parameter, δ, which scales the resolution by allowing for target localization with sub wavelength accuracy. Numerical results in two dimensions illustrate the robustness of the approach for imaging multiple targets. However, the depth at which targets are detectable is limited due to the absorption in the lossy medium.

A transcription factor-based bacterial biosensor system and its application for on-site detection of explosives

Detecting unexploded landmines is critical due to the environmental pollution and potential humanitarian risks caused by buried landmines. Therefore, this study focused on developing a biosensor system capable of detecting explosives safely and efficiently. A novel transcription factor-based Escherichia coli biosensor was designed to detect 1,3-dinitrobenzene (1,3-DNB). The MexT transcription factor from Pseudomonas putida (P. putida) was identified as the fundamental sensing element in this biosensor. The study found that MexT positively regulated the transcription of PP_2827 by binding to the bidirectional promoter region between them, and significantly enhanced the expression of downstream genes under the condition of 1,3-DNB. The MexT-based biosensor for 1,3-DNB was developed by adopting different combinations of the mexT gene and promoters. The optimized biosensor demonstrated adequate sensitivity for detecting 0.1 μg/mL of 1,3-DNB in a liquid solution with satisfactory specificity and long-term stability. Subsequently, the MexT-based biosensor was integrated into a detection device to simulate the in-field exploration of explosives. The system exhibited a detection sensitivity of 0.5 mg/kg for 1,3-DNB in the sand, and realized the detection of on-site and large-scale area and the location of buried 1,3-DNB under the soil. The study provided a novel transcription factor-based bacterial biosensor and a complete system (China Earth Eye, CEE) for sensitive detection of 1,3-DNB. The good performance of this biosensor system can facilitate the development of accurate, on-site, and high-efficient exploration of explosives in real extensive minefields. Moreover, this 1,3-DNB biosensor can be complementary to the 2,4-DNT biosensor reported before, demonstrating its potential applications in military situations.

Eco‐friendly and Efficient Synthesis of Water‐soluble MoS2 Quantum Dot Probe for Smart Explosive Sensors

AbstractThe rapid detection of buried landmines has become a crucial concern of global security owing to the advancement in terrorist attacks. Indeed, the development of smart materials for the rapid detection of explosives especially nitro‐explosives is the need of time. However, the sensitivity and selectivity of materials for the detection of nitro‐explosives are major hurdles due to their low vapour pressure at room temperature. Albeit, it could be resolved by the use of advanced functional nanomaterials bearing high surface area and excellent optoelectronic properties. In this context, the water‐soluble MoS2 quantum dots (QDs) are synthesized by an ultrafast eco‐friendly hot injection method and potentially used for the detection of nitro‐explosives. The detection of picric acid (PA), 2,4,6‐Trinitrotoluene (TNT) and various other nitroaromatic compounds is performed by fluorescent probe technique. Notably, MoS2 QDs have effectively detected picric acid and TNT exhibiting detection limits of 5.13 ppm and 43.93 ppm respectively in water via a photoinduced electron transfer mechanism. Real‐time analysis of picric acid employing a paper strip of MoS2 QD as a fluorescent probe clearly demonstrates MoS2 QDs′ potential for practical usage in explosive detection. This work is patented: Application No. 202121000715 (applied).

Design of Unmanned Landmine Detection Vehicle Using Arduino

The concept presented in this article revolves around the idea of an economically designed UGV (Unmanned Ground Vehicle) for the demining process. Landmine discovery is a critical area of exploration due to the high number of losses and injuries caused by landmines each time. The developed technology generally requires human assistance nearby for landmine detection. Every so often the military bear loss of their equipment specialists. Also, false detection leads to the wastage of resources invested in the technology. Our prime aim is to develop a sturdy design for UGV which require minimum assembly time i.e., “Ready-to-Assemble” concept. This paper outlines the design of a UGV equipped with IR sensor, and metal detector and controlled using Arduino microcontroller. The Arduino microcontrollers are programmed to control the UGV’s movements and the sensor data processing. The UGV is built on a six-wheel drive controlled by two motor drivers, which is equipped with IR sensor to detect the heat signature of buried landmines and a metal detector to detect metallic landmines. The GPS location of the landmine is sent directly to a mobile device using a GSM Module. The UGV is controlled using Bluetooth remotely. The design of the vehicle was performed on Solidworks, CAD software. The software was used to design the chassis, suspension system, and other components such as the metal detector and IR sensor mounts. Proteus software was used to stimulate the electronic circuitry. The UGV has potential applications in detecting and removing landmines safely, minimizing the risk of human casualties. Future work could involve improving the system's accuracy and efficiency to make it a more effective tool for landmine detection and removal.

Performance upgrade of a microbial explosives’ sensor strain by screening a high throughput saturation library of a transcriptional regulator

We present a methodology for a high-throughput screening (HTS) of transcription factor libraries, based on bacterial cells and GFP fluorescence. The method is demonstrated on the Escherichia coli LysR-type transcriptional regulator YhaJ, a key element in 2,4-dinitrotuluene (DNT) detection by bacterial explosives’ sensor strains. Enhancing the performance characteristics of the YhaJ transcription factor is essential for future standoff detection of buried landmines. However, conventional directed evolution methods for modifying YhaJ are limited in scope, due to the vast sequence space and the absence of efficient screening methods to select optimal transcription factor mutants. To overcome this limitation, we have constructed a focused saturation library of ca. 6.4 × 107 yhaJ variants, and have screened over 70 % of its sequence space using fluorescence-activated cell sorting (FACS). Through this screening process, we have identified YhaJ mutants exhibiting superior fluorescence responses to DNT, which were then effectively transformed into a bioluminescence-based DNT detection system. The best modified DNT reporter strain demonstrated a 7-fold lower DNT detection threshold, a 45-fold increased signal intensity, and a 40 % shorter response time compared to the parental bioreporter. The FACS-based HTS approach presented here may hold a potential for future molecular enhancement of other sensing and catalytic bioreactions.

Landmine-identification system based on the detection of scattered neutrons: A feasibility study

The feasibility study of the landmine identification system (LIS) based on the angular distribution of thermal neutrons for buried landmines was undertaken in this work. The operation of the system was based on both artificial neural networks (ANN) and least-squares methods in which the input data were prepared by the MCNP6.1 Monte Carlo code before feeding into MATLAB and dedicated programs, respectively. Having achieved the promising ANN and least-squares results (with a relative error of less than 15%), the study confirmed that the proposed system is sensitive to the depth of the landmine as well as to the soil moisture, therefore it could be used for landmine identification.

Introduction of quorum sensing elements into bacterial bioreporter circuits enhances explosives' detection capabilities.

A possible solution for the standoff detection of buried landmines is based on the use of microbial bioreporters, genetically engineered to emit a remotely detectable optical signal in response to trace amounts of explosives’ signature chemicals, mostly 2,4‐dinitrotoluene (DNT). Previously developed DNT sensor strains were based on the fusion of a DNT‐inducible gene promoter to a reporting element, either a fluorescent protein gene or a bacterial bioluminescence gene cassette. In the present study, a different approach was used: the DNT‐inducible promoter activates, in Escherichia coli, the quorum‐sensing luxI and luxR genes of Aliivibrio fischeri. N‐Acyl homoserine lactone (AHL), synthesized by LuxI, combines with LuxR and activates the bioluminescence reporter genes. The resulting bioreporter displayed a dose‐dependent luminescent signal in the presence of DNT. Performance of the sensor strain was further enhanced by manipulation of the sensing element (combining the E. coli DNT‐inducible azoR and yqjF gene promoters), by replacing the luminescence gene cassette of Photorhabdus luminescens luxCDABE with A. fischeri luxCDABEG, and by introducing two mutations, eutE and ygdD, into the host strain. DNT detection sensitivity of the final bioreporter was over 340‐fold higher than the original construct.

Enhancing DNT Detection by a Bacterial Bioreporter: Directed Evolution of the Transcriptional Activator YhaJ.

Detection of buried landmines is a dangerous and complicated task that consumes large financial resources and poses significant risks to the personnel involved. A potential alternative to conventional detection methodologies is the use of microbial bioreporters, capable of emitting an optical signal upon exposure to explosives, thus revealing to a remote detector the location of buried explosive devices. We have previously reported the design, construction, and optimization of an Escherichia coli-based bioreporter for the detection of 2,4,6-trinitrotoluene (TNT) and its accompanying impurity 2,4-dinitrotoluene (DNT). Here we describe the further enhancement of this bioreporter by the directed evolution of YhaJ, the transcriptional activator of the yqjF gene promoter, the sensing element of the bioreporter’s molecular circuit. This process resulted in a 37-fold reduction of the detection threshold, as well as significant enhancements to signal intensity and response time, rendering this sensor strain more suitable for detecting the minute concentrations of DNT in the soil above buried landmines. The capability of this enhanced bioreporter to detect DNT buried in sand is demonstrated.

UAV-Borne FMCW InSAR for Focusing Buried Objects

Antipersonnel mines are hidden weapons that are usually buried close to the surface and are triggered by a foot step of the victim. A sensor that is able to detect minimum metal mines is a ground penetrating synthetic aperture radar (GPSAR). In previous work, an unmanned aerial vehicle (UAV)-based GPSAR was developed and tested for the detection of buried landmines. The real topography was neglected and the interface between air and soil was assumed as a horizontal plane surface. Since the dielectric properties of the soil reduce the propagation velocity of the electromagnetic wave, the interface between air and soil has to be known precisely for subsurface focusing. Neglecting the surface profile has a negative impact on the image quality and prevents the detection of buried objects. In this letter, a novel two-step procedure is used to overcome this issue. In time-division multiplex mode, the radar transmits two frequency-modulated ramps in two different frequency bands. The data of the upper frequency band are used to generate a digital elevation model (DEM) through interferometry. The data of the lower frequency band are used for GPSAR focusing on the basis of the DEM. It is demonstrated that the GPSAR image quality is improved on nonideal planar surfaces and the probability of detection is increased.

Improving Detection of a Portable NQR System for Humanitarian Demining Using Machine Learning

This article presents an approach to enhance the detection of buried landmines by applying machine learning (ML) to signals from a nuclear quadrupole resonance (NQR) system. This custom-made, low-cost, and portable NQR system has been developed for deployment in humanitarian demining, where strong radio frequency (RF) interference and a low signal-to-noise ratio (SNR) are important challenges for accurate detection. To tackle these problems, we have applied and tested various ML techniques to NQR signals acquired by our system in laboratory experiments with the explosive Research Department X (RDX). Results suggest that ML methods can indeed improve the detection accuracy of the NQR device, and this is confirmed further using data from field trials with our device. Importantly, the trained classifiers can be implemented with our device’s field-programmable gate array (FPGA) architecture and can run with little time penalty compared with simpler but less-efficient fast Fourier transform (FFT)-based energy detection methods.

Sense and sensibility: of synthetic biology and the redesign of bioreporter circuits.

Sense and sensibility: of synthetic biology and the redesign of bioreporter circuits.

A bacterial bioreporter for the detection of 1,3,5-trinitro-1,3,5-triazinane (RDX).

We report the design, construction, and testing of Escherichia coli-based bioluminescent bioreporters for the detection of 1,3,5-trinitro-1,3,5-triazinane (RDX), one of the most prevalent military-grade explosives in use today. These sensor strains are based on a fusion between the promoter of either the hmp (nitric oxide dioxygenase) or the hcp (a high-affinity nitric oxide reductase) E. coli gene, to the microbialbioluminescence luxCDABEG gene cassette. Signal intensity was enhanced in ∆hmp and ∆hcp mutants, and detection sensitivity was improved when the two gene promoters were cloned in tandem. The Photobacterium leiognathi luxCDABEG reporter genes were superior to those of Aliivibrio fischeri in terms of signal intensity, but in most cases inferior in terms of detection sensitivity, due to a higher background signal. Both sensor strains were also induced by additional nitro-organic explosives, as well as by nitrate salts. Sensitive detection of RDX in a solid matrix (either LB agar or sand) was also demonstrated, with the bioreporters encapsulated in 1.5-mm calcium alginate beads. Lowest RDX concentration detected in sand was 1.67mg/kg sand. The bioreporter strains described herein may serve as a basis for a standoff detection technology of RDX-based explosive devices, including buried landmines.

IOT based Land Mine Detection Robot

Such equipment is usually automatically blasted through pressure when a target steps on it or drives on it. Demining or mine clearance is the process of removing land mines from an area, while minesweeping describes the task of locating mines. Landmines are generally easy to lay and difficult and dangerous. They are harmful due to their unknown positions and are often difficult to detect. Although dimming has been given the highest priority, currently my clearing operation is a labor-intensive, slow, very dangerous, expensive and low technology operation. The current rate of human quarry is about 100 thousand per year. The idea is to build and develop an automated robot capable of detecting buried landmines and taking them from their locations, enabling the operator to control the robot from afar. The buried quarry is detected using metal detectors as most land mines have metal components. The robot will travel in a straight line route. The system allows the operator to stay at a safe distance by enabling the robot to safely control. Wireless control is for the safety of the operator, designed robots must be able to operate remotely, and is equipped with wireless data transmission capabilities.

An autonomous bioluminescent bacterial biosensor module for outdoor sensor networks, and its application for the detection of buried explosives

We describe a miniaturized field-deployable biosensor module, designed to function as an element in a sensor network for standoff monitoring and mapping of environmental hazards. The module harbors live bacterial sensor cells, genetically engineered to emit a bioluminescent signal in the presence of preselected target materials, which act as its core sensing elements. The module, which detects and processes the biological signal, composes a digital record that describes its findings, and can be transmitted to a remote receiver. The module is an autonomous self-contained unit that can function either as a standalone sensor, or as a node in a sensor network. The biosensor module can potentially be used for detecting any target material to which the sensor cells were engineered to respond. The module described herein was constructed to detect the presence of buried landmines underneath its footprint. The demonstrated detection sensitivity was 0.25 mg 2,4-dinitrotoluene per Kg soil.

The Escherichia coli azoR gene promoter: A new sensing element for microbial biodetection of trace explosives

Abstract DNT (2,4-dinitrotoluene), a volatile impurity in military grade TNT-based explosives, is a potential tracer for the detection of buried landmines and other explosive devices. We have previously described DNT bioreporter strains, based on a fusion between the Escherichia coli yqjF gene promoter to either a bacterial luxCDABE luminescence gene cassette or to the green fluorescent protein gene gfp. We now present the azoR gene promoter, demonstrated to be strongly induced by DNT, as an alternative sensing element for this compound. An E. coli bioreporter strain harboring a plasmid-borne fusion of the azoR promoter region to Photorhabdus luminescens luxCDABE displayed stronger bioluminescent responses to DNT than the yqjF-based bioreporter. The azoR promoter was induced not directly by DNT but by its degradation products; the most potent inducer was 2,4,5-trihydroxytoluene (THT). This reaction was positively regulated by YhaJ, a member of the LysR family of transcriptional regulators, and was significantly amplified in a yhaK mutant. We also show that DNT degradation in E. coli involves glutathione, which plays a vital role in azoR gene promoter activation.

Detection of buried explosives with immobilized bacterial bioreporters.

The unchecked dispersal of antipersonnel landmines since the late 19th century has resulted in large areas contaminated with these explosive devices, creating a substantial worldwide humanitarian safety risk. The main obstacle to safe and effective landmine removal is the identification of their exact location, an activity that currently requires entry of personnel into the minefields; to date, there is no commercialized technology for an efficient stand-off detection of buried landmines. In this article, we describe the optimization of a microbial sensor strain, genetically engineered for the remote detection of 2,4,6-trinitrotoloune (TNT)-based mines. This bioreporter, designed to bioluminescence in response to minute concentrations of either TNT or 2,4-dinitotoluene (DNT), was immobilized in hydrogel beads and optimized for dispersion over the minefield. Following modifications of the hydrogel matrix in which the sensor bacteria are encapsulated, as well as their genetic reporting elements, these sensor bacteria sensitively detected buried 2,4-dinitrotoluene in laboratory experiments. Encapsulated in 1.5mm 2% alginate beads containing 1% polyacrylic acid, they also detected the location of a real metallic antipersonnel landmine under field conditions. To the best of our knowledge, this is the first report demonstrating the detection of a buried landmine with a luminescent microbial bioreporter.

Acoustic excitation of landmines and remote sensing from a moving truck

The U.S. Department of Defense developed a 960 pixel laser Doppler vibrometer to capture seismic vibration and detect buried landmines. The sensor relied on a loudspeaker to create the seismic disturbances. This system captured seismic spatial responses while advancing at 1 m/s at 30 m standoff. Automated target recognition algorithms quickly processed the spatial vibration data to warn operators of threats. Sensor noise was highly variable, but on the order of .05mm/s in a band 50–400 Hz over which the sensor operated. Inertial sensing reduced gross Doppler components common to all channels. Even with these corrections, channel dropouts remained a challenge, so filtering of erroneous samples in time and space was required to improve the data quality, which is possible due to 960 simultaneous spatial samples. The large pixel count permitted road scans of 2 m × 1 km in less than 30 min. The system proved effective at finding buried threats that produced seismic anomalies at the surface, but additional challenges lie in differentiating target responses from clutter. This presentation will introduce the system and display high-resolution seismic images excited acoustically. It will also illustrate an acoustic wave captured directly by the lasers as the air's index-of-refraction fluctuated.

Genome-wide gene-deletion screening identifies mutations that significantly enhance explosives vapor detection by a microbial sensor

Genetically engineered microbial biosensors, capable of detecting traces of explosives residues above buried military ordnance and emitting an optical signal in response, may potentially serve for the standoff detection of buried landmines. A promising candidate for such an application is a previously reported Escherichia coli-based reporter strain that employs the yqjF gene promoter as its sensing element; however, for this sensor to be able to detect actual landmines reliably, it was necessary for its detection sensitivity and signal intensity to be enhanced. In this study, a high-throughput approach was employed to screen the effects of individual gene deletions on yqjF activation by 2,4-dinitrotoluene (DNT). Several genes were identified, the deletion of which elicited a significant enhancement of yqjF induction by DNT. The most promising of these mutations were introduced into the sensor strain, individually or in pairs, yielding a considerable increase in signal intensity and a lowering of the detection threshold. A strain harboring two of the identified mutations, ygdD and eutE, appears to be the most sensitive microbial biosensor currently described for the detection of traces of landmine explosives.

Landmine Detection Using Autoencoders on Multipolarization GPR Volumetric Data

Buried landmines and unexploded remnants of war are a constant threat for the population of many countries that have been hit by wars in the past years. The huge amount of casualties has been a strong motivation for the research community toward the development of safe and robust techniques designed for landmine clearance. Nonetheless, being able to detect and localize buried landmines with high precision in an automatic fashion is still considered a challenging task due to the many different boundary conditions that characterize this problem (e.g., several kinds of objects to detect, different soils and meteorological conditions, etc.). In this article, we propose a novel technique for buried object detection tailored to unexploded landmine discovery. The proposed solution exploits a specific kind of convolutional neural network (CNN) known as autoencoder to analyze volumetric data acquired with ground penetrating radar (GPR) using different polarizations. This method works in an anomaly detection framework, indeed we only train the autoencoder on GPR data acquired on landmine-free areas. The system then recognizes landmines as objects that are dissimilar to the soil used during the training step. Experiments conducted on real data show that the proposed technique requires little training and no ad hoc data preprocessing to achieve accuracy higher than 93% on challenging data sets.

A Lightweight and Low-Power UAV-Borne Ground Penetrating Radar Design for Landmine Detection.

This paper presents the development of a lightweight and low-power Ground Penetrating Radar (GPR) to detect buried landmines in harsh terrain, using an Unmanned Aerial Vehicle (UAV). Despite the fact that GPR airborne systems have been already used for a while, there has yet been no focus on the UAV autonomy, which depends on the payload itself. Therefore, the contribution of this work is the introduction of a lightweight and low-power consumption GPR system, which is based on the Stepped Frequency Continuous Wave (SFCW) radar principle. The Radio Frequency (RF) transceiver represents an improved implementation of the super-heterodyne architecture, which currently offers higher sensitivity. This is achieved by combining analog and digital processing techniques. The experimental results showed that the developed system can detect both metallic and plastic buried targets. Target detection with a scanning height up to about 0.5 m shows good applicability in an unstructured, harsh environment, which is typical of mined terrain. The proposed system still needs some improvements for a fully operational system regarding different aspects of scanning speeds and soil properties such as moisture content.