Unexploded Ordnance Detection Research Articles

Enhancement of Magnetic Data by Stable Downward Continuation for UXO Application

The magnetic method has been proven to be a successful geophysical tool for the detection of unexploded ordnance (UXO). Aeromagnetic surveys are advantageous since they can acquire data over large areas. The downside is that magnetic anomalies due to multiple metallic targets can overlap significantly due to flight height restrictions. Such overlap combined with the acquisition noise may significantly decrease the signal-to-noise ratio of data. These adverse effects can mask the true level of contamination at a site during the initial assessment based on the magnetic method as well as decrease the overall effectiveness of discrimination during the active clearance stage. We propose a method to ameliorate these difficulties using stable downward continuation, which reconstructs the field at a lower observation height from the observed data. The stable algorithm formulates the downward continuation as an inverse problem and incorporates the expected power spectrum of UXO anomalies. The power spectrum preserves the spectral properties and subdues the amplification of high-frequency noise. Synthetic and field examples show that the algorithm can reliably reconstruct the magnetic anomaly at the ground surface within the limitation imposed by the noise. The reconstructed field exhibits significant enhancement compared to the original data.

High-<i>T<sub>c</sub></i> Superconducting Electronic Devices Based on YBCO Step-Edge Grain Boundary Junctions

We outline a number of high temperature superconducting Josephson junction-based devices including superconducting quantum interference devices (SQUIDs) developed for a wide range of applications including geophysical exploration, magnetic anomaly detection, terahertz (THz) imaging and microwave communications. All these devices are based on our patented technology for fabricating YBCO step-edge junction on MgO substrates. A key feature to the successful application of devices based on this technology is good stability, long term reliability, low noise and inherent flexibility of locating junctions anywhere on a substrate. key words: Josephson junction, grain boundary step edge junction, high temperature superconductor, SQUID, THz imaging, mineral exploration, magnetic anomaly detection, unexploded ordnance detection, microwave devices

Waveguide properties recovered from shallow diffractions in common offset GPR

[1] Near-surface heterogeneities produce diffractions in common offset ground-penetrating radar (GPR) data from the Gnangara Groundwater Mound, north of Perth, Western Australia. These diffracted wavefields can be enhanced and show a dispersion pattern if they propagate along a waveguide caused by a low velocity surface layer, such as moist sand on top of dry sand. Until now, GPR waveguide dispersion has been analyzed and inverted using common midpoint data. Using numerical modeling, we demonstrate that the same dispersion information can also be recovered from a diffracted electromagnetic wavefield recorded with common offset geometry. Frequency-slowness analysis of shallow diffractions in common offset GPR field data reveals high resolution dispersion curves. Inverting picked dispersion maxima to modeled curves (i.e., modal wave propagation in waveguide layer) allows estimation of waveguide height and velocities of waveguide and the underlying material. Data analysis in the frequency-wavenumber domain provides an alternative technique for extracting dispersion curves. Preliminary results validate this approach, which could be favorable in large-scale applications due to minimal processing requirement and inherent yet adjustable spatial averaging. The differences between waveguide parameters recovered from two surveys appear to be consistent with seasonal changes in moisture content and lateral changes due to variations in depositional environment. Our approach presents a new method to quantify the shallow dielectric permittivity structure of the subsurface from common offset gathers—the most commonly acquired type of GPR data. Potential applications of this method include estimation of shallow moisture distribution, early target identification for unexploded ordnance (UXO) detection, concrete slab characterization, pedological investigations, or planetary exploration.

Detection of unexploded ordnance by PGNAA based borehole-logging

The performance of a borehole-logging system, based on prompt-gamma-neutron-activation-analysis (PGNAA), for explosive detection was studied by Monte-Carlo simulations. The prompt gamma of nitrogen, which is a constituent of common explosive, was used to identify the unexploded ordnance (UXO). Our results show that the minimum counting time depends on the soil moisture, the cladding thickness and the explosive composition. In conjunction with the standard detection by magnetometry, the PGNAA is a promising analytical technique for definitive identification of deep buried UXOs.

Joint diagonalization applied to the detection and discrimination of unexploded ordnance

Efforts to discriminate buried unexploded ordnance from harmless surrounding clutter are often hampered by the uncertainty in the number of buried targets that produce a given detected signal. We present a technique that helps determine that number with no need for data inversion. The procedure is based on the joint diagonalization of a set of multistatic response (MSR) matrices measured at different time gates by a time-domain electromagnetic induction sensor. In particular, we consider the Naval Research Laboratory’s Time-Domain Electromagnetic Multisensor Towed Array Detection System (TEMTADS), which consists of a [Formula: see text] square grid of concentric transmitter/receiver pairs. The diagonalization process itself generalizes one of the standard procedures for extracting the eigenvalues of a single matrix; in terms of execution time, it is comparable to diagonalizing the matrices one by one. We present the method, discuss and illustrate its mathematical basis and physical meaning, and apply it to several actual measurements carried out with TEMTADS at a test stand and in the field at the former Camp Butner in North Carolina. We find that each target in a measurement is associated with a set of nonzero time-dependent MSR eigenvalues (usually three), which enables estimation of the number of targets interrogated. These eigenvalues have a characteristic shape as a function of time that does not change with the location and orientation of the target relative to the sensor. We justify analytically and empirically that symmetric targets have pairs of eigenvalues with constant ratios between them.

Cart-Mounted Geolocation System for Unexploded Ordnance With Adaptive ZUPT Assistance

Reliable and precise navigation technology is essential for robust detection and discrimination of unexploded ordnance (UXO) in a wide range of field conditions, including GPS-challenged environment. Based on the fact that the UXO detection involves frequent stops, this paper proposes an adaptive ZUPT (AZUPT) algorithm in a sliding time window to guarantee the correct identification of the zero velocity condition and improve the position accuracy of UXO geolocation. Furthermore, a known zero velocity-based prefiltering method is used to remove INS sensor errors. A pushcart-based prototype in which the tactical-grade inertial measurement unit and geodetic-grade GPS receiver are mounted is designed for the geolocation system. Field test was undertaken, and simulated GPS outages were introduced to the data. The result shows that AZUPT precisely identified the zero velocity and greatly improved the positioning accuracy of the cart-mounted UXO geolocation system.

Historical Development and Performance of Airborne Magnetic and Electromagnetic Systems for Mapping and Detection of Unexploded Ordnance

Over the past fifteen years, notable progress has been made in the performance of airborne geophysical systems for mapping and detection of unexploded ordnance in terrestrial and shallow marine environments. For magnetometer systems, the most significant improvements include development of boom-mounted platforms, and implementation of higher sample rates, denser magnetometer arrays, and vertical gradient configurations. Nine magnetometer-based systems are described and their performance summarized. In prototype analyses and recent U.S. Department of Defense Environmental Security Technology Certification Program (ESTCP) assessments using new production systems, the best performance has been achieved with a vertical gradient configuration. As effective as magnetometer systems have proven to be at many sites, they are inadequate at sites where basalts and other ferrous geologic formations or soils produce anomalies that approach or exceed those of target ordnance items. Additionally, magnetometer systems are ineffective where detection of non-ferrous ordnance items is of primary concern. We discuss the development of airborne time-domain electromagnetic systems over the past ten years. Overall, improvements in airborne geophysical systems have led to more consistent detection of smaller ordnance. These trends should continue as additional technological advances are made.

Subsurface electromagnetic induction imaging for unexploded ordnance detection

Detection and classification of unexploded ordnance based on electromagnetic induction have made tremendous progress over the last few years, to the point that not only more realistic terrains are being considered but also more realistic questions – such as when to stop digging – are being posed. Answering such questions would be easier if it were somehow possible to see under the surface. In this work we propose a method that, within the limitations on resolution imposed in the available range of frequencies, generates subsurface images from which the positions, relative strengths, and number of targets can be read off at a glance. The method seeds the subsurface with multiple dipoles at known locations that contribute collectively but independently to the measured magnetic field. The polarizabilities of the dipoles are simultaneously updated in a process that seeks to minimize the mismatch between computed and measured fields over a grid. In order to force the polarizabilities to be positive we use their square roots as optimization variables, which makes the problem nonlinear. The iterative update process guided by a Jacobian matrix discards or selects dipoles based on their influence on the measured field. Preliminary investigations indicate a fast convergence rate and the ability of the algorithm to locate multiple targets based on data from various state-of-the-art electromagnetic induction sensors.

COMBINING ADVANCES IN EM INDUCTION INSTRUMENTATION AND INVERSION SCHEMES FOR UXO CHARACTERIZATION

Several experimental time-domain EM induction instru- ments have recently been developed for unexploded ordnance (UXO) detection and characterization that use multiple transmitting and re- ceiving coil combinations. One such system, the US Geological Sur- vey's ALLTEM system, is unique in that it measures both the electro- dynamic response (i.e., induced eddy currents) and the magneto-static response (i.e., induced magnetization). This allows target characteri- zation based on the dyadic polarizability of both responses. This pa- per examines the numerical response of the ALLTEM instrument due to spheroidal, conductive, and permeable UXO targets; and to con- ductive and optionally viscous magnetic earth. An inversion scheme is presented for spheroidal targets that incorporates fully polarimet- ric measurements for both magneto-static and electro-dynamic excita- tions. The performance of the inversion algorithm is evaluated using both simulated and surveyed data. The results are examined as a function of the number of coil combinations, number of instrument lo- cations, and uncertainty in sensor location and orientation. Results from the speciflc cases tested (prolate spheroids lying horizontally) show that 1) that collecting data from more than 12 sensor locations or from more than four coil combinations reduced the chances that inversion solutions would be from a local minimum, and 2) that un- certainties in position greater than 3cm or in orientation greater than 10 degrees cause errors in the estimated spheroid principal lengths of greater than 100%. Soil conductivities less than 1S/m contribute neg- ligible interference to the target response, but viscous magnetic soils with permeabilities greater than 10 i6 MKS units do cause detrimental interference.

An Introduction to Applied and Environmental Geophysics

The book covers a range of applications including mineral, hydrocarbon and groundwater exploration, and emphasises the use of geophysics in civil engineering and in environmental investigations. Following on from the international popularity of the first edition, this new, revised, and much expanded edition contains additional case histories, and descriptions of geophysical techniques not previously included in such textbooks. The level of mathematics and physics is deliberately kept to a minimum but is described qualitatively within the text. Relevant mathematical expressions are separated into boxes to supplement the text. The book is profusely illustrated with many figures, photographs and line drawings, many never previously published. Key source literature is provided in an extensive reference section; a list of web addresses for key organisations is also given in an appendix as a valuable additional resource. Covers new techniques such as Magnetic Resonance Sounding, Controlled- Source EM, shear-wave seismic refraction, and airborne gravity and EM techniques -- Now includes radioactivity surveying and more discussions of down-hole geophysical methods; hydrographic and Sub-Bottom Profiling surveying; and Unexploded Ordnance detection -- Expanded to include more forensic, archaeological, glaciological, agricultural and bio-geophysical applications -- Includes more information on physio-chemical properties of geological, engineering and environmental materials.

A Robust Solution to High-Accuracy Geolocation: Quadruple Integration of GPS, IMU, Pseudolite, and Terrestrial Laser Scanning

Reliable and accurate geolocation is essential for airborne and land-based remote sensing applications. The detection, discrimination, and remediation of unexploded ordnance (UXO) and other munitions and explosives of concern (MEC) using the currently available detection and geolocation technologies often yield unsatisfactory results, failing to detect all MEC present at a site or to discriminate between MEC and nonhazardous items. Thus, the goal of this paper is to design and demonstrate a high-accuracy geolocation methodology that will address centimeter-level relative accuracy requirements of a man-portable electromagnetic (EM) sensor system in open and impeded environments. The proposed system design is based on the tight quadruple integration of the Global Positioning System (GPS), the inertial measurement unit (IMU) system, the terrestrial radio-frequency (RF) system pseudolite (PL), and terrestrial laser scanning (TLS) to support high-accuracy geolocation for a noncontact EM mapping system in GPS-challenged environments. The key novel component of the proposed multisensor system is the integration of TLS that can provide centimeter-level positioning accuracy in a local frame and thus enables a GPS/IMU/PL-based navigation system to achieve both high absolute and relative positioning accuracy in GPS-impeded environments. This paper presents the concept design of the quadruple integration system, the algorithmic approach to data integration with a special emphasis on TLS integration with GPS/IMU/PL, and the performance assessment based on real data, where centimeter-level relative geolocation accuracy is demonstrated during the GPS signal blockage.

Exploiting multiple sensor modalities for classification of underwater munitions: A Dempster–Shafer theoretic approach

Detection and classification of underwater UXOs (UneXploded Ordnance) is a task that is receiving considerable attention from the DoD and related agencies that are involved in management of military munitions. Achieving a reasonable accuracy in detection and classification of these objects is extremely difficult mainly due to the harsh cluttered underwater environment. It is now an accepted fact that no single sensing technology can be both accurate and cost-effective. Low visibility in underwater exposes a significant limitation to optical cameras which are usually better suited for identifying the physical shape of objects. While acoustic imaging is a good alternative, the characteristics of imaging and physical system artifacts make the object recognition task non-trivial. Multi-sensory fusion provides an avenue to exploit the strengths of individual sensors and modalities while mitigating their weaknesses. We address the problem of fusion of multiple sensory information for the task of underwater UXO detection via the use of a Dempster–Shafer (DS) theoretic evidence fusion scheme. The DS theoretic foundation of our fusion algorithm also enables it to incorporate domain expert opinions and knowledge from databases to assist in the detection and classification tasks. We illustrate this method via the use of real data obtained at a test site located in the Florida Atlantic University premises.

Effects of low-pass filtering on the calculated structural index from magnetic data

Euler and extended Euler deconvolution applications use an assumed structural index (SI) or calculate the SI, respectively, for magnetic anomaly data within a specified window. The structural index depends on the source type: specifically, the rate at which the field produced by the source decays. We have examined the effects that the application of low-pass filtering to magnetic data has on estimating the SI. Using a simple low-pass filter, we derived the SI for filtered-field solutions directly over, and away from, a target based on the magnetic potential of a vertical dipole [Formula: see text]. We validated this approach by applying extended Euler deconvolution to synthetic and field examples. In general, filtered magnetic data will decrease the numerically determined SI to a value lower than the theoretical one. The slope and cutoff wavelength of the filter directly affect the estimated SI solutions. The results prove that one must take into account filtering for the application of Euler deconvolution to locate dipole anomalies for unexploded ordnance detection.

Applied behavior analysis is ideal for the development of a land mine detection technology using animals.

The detection and subsequent removal of land mines and unexploded ordnance (UXO) from many developing countries are slow, expensive, and dangerous tasks, but have the potential to improve the well-being of millions of people. Consequently, those involved with humanitarian mine and UXO clearance are actively searching for new and more efficient detection technologies. Remote explosive scent tracing (REST) using trained dogs has the potential to be one such technology. However, details regarding how best to train, test, and deploy dogs in this role have never been made publicly available. This article describes how the key characteristics of applied behavior analysis, as described by Baer, Wolf and Risley (1968, 1987), served as important objectives for the research and development of the behavioral technology component of REST while the author worked in humanitarian demining.

Results of a high-resolution airborne TEM system demonstration for unexploded ordnance detection

Airborne geophysical sensor systems using boom-mounted configurations now play an important role in characterizing ordnance-contaminated defense sites. Most of the systems developed to date have been magnetometer systems. These have proven ineffective at sites where basalt or other magnetic geologic units or soils have caused unacceptable noise in the data. Electromagnetic (EM) systems have been developed as an alternative to magnetometer systems for such sites. Recent evaluation of New Mexico field results from the new TEM-8 time-domain EM system has shown successful detection of emplaced blind-seeded ordnance items. Overall, 109 of 110 items were detected, some as small as [Formula: see text] mortars at an area with moderately magnetic geology. The TEM-8 system was also effective in mapping ordnance at a bombing target with severe geologic interference due to basalt, where a previous airborne magnetometer survey proved ineffective. Data and performance metrics for both survey areas are presented and evaluated.

Ultrawideband Synthetic Aperture Radar Unexploded Ordnance Detection

Airborne ultrawideband (UWB) synthetic aperture radar (SAR) can perform wide-area detection of unexploded ordnance (UXO) to locate former bombing ranges efficiently. Two main issues in UWB SAR UXO detection, feature extraction, and discriminator design are considered. A space-wavenumber distribution and moment invariants-based method is proposed to extract the multi-aspect feature of UXO with both amplitude and spatial distribution information. Based on the extracted feature, a support vector machine (SVM) with hypersphere classification boundary, referred to as HS-SVM, is used as the UXO discriminator, which can be trained with a small training set of only UXO samples. Furthermore, the problem of HS-SVM kernel choice is studied, and the hidden Markov model (HMM) kernel is proved to be better than the Gaussian kernel. The efficiency of the proposed feature extraction method and the HMM kernel HS-SVM is validated using real data collected by a UWB SAR system.

Dual-mode, Fluxgate-Induction Sensor for UXO Detection and Discrimination

We describe an innovative, dual-mode, fluxgate-induction sensor (FIS) that combines a DC magnetometer and an electromagnetic (EM) sensor. This sensor will enable one-pass unexploded ordnance (UXO) detection and discrimination using the joint measurements. The FIS is based on a [Formula: see text] long, high-permeability magnetic core and a sensing coil that are shared by both EM and magnetic (MAG) modes. This integration makes the sensor very compact and removes the potential crosstalk problem of the core material of one sensor dominating the response of the other. A prototype receiver was developed and true serial, dual-mode operation demonstrated. The FIS achieved sensitivities of [Formula: see text] rms in MAG mode and [Formula: see text] at [Formula: see text] in EM mode, which compare favorably to existing commercial instruments. Triaxial dipole modeling confirms that three-component EM data are better for shape characterization than one (vertical) component. Assuming axisymmetry, inversions of three-component EM measurements of 22 cylindrical and disk-shaped targets yielded 100% correct classification of UXO-like objects (cylinders) and 38% misclassification of disks as cylinders. Degraded classification performance with increasing vertical distance may be caused by the small cross-sectional area of the FIS; an array will provide better field sampling. Triaxial dipole modeling of the MAG data confirmed its utility for detecting deeper targets using only the vertical component. Based on these results, the FIS is ready for field demonstration and validation.

Realistic Subsurface Anomaly Discrimination Using Electromagnetic Induction and an SVM Classifier

The environmental research program of the United States military has set up blind tests for detection and discrimination of unexploded ordnance. One such test consists of measurements taken with the EM-63 sensor at Camp Sibert, AL. We review the performance on the test of a procedure that combines a field-potential (HAP) method to locate targets, the normalized surface magnetic source (NSMS) model to characterize them, and a support vector machine (SVM) to classify them. The HAP method infers location from the scattered magnetic field and its associated scalar potential, the latter reconstructed using equivalent sources. NSMS replaces the target with an enclosing spheroid of equivalent radial magnetization whose integral it uses as a discriminator. SVM generalizes from empirical evidence and can be adapted for multiclass discrimination using a voting system. Our method identifies all potentially dangerous targets correctly and has a false-alarm rate of about 5%.

Automatic detection of UXO magnetic anomalies using extended Euler deconvolution

We have developed an algorithm for the automatic detection of prospective unexploded ordnance (UXO) anomalies in total-field or gradient magnetic data based on the concept of the structural index (SI) of a magnetic anomaly. Identifying magnetic anomalies having specific structural indices enables the direct detection of potential UXO targets. The total magnetic field produced by a dipolelike source, such as a UXO, decays with inverse distance cubed and therefore has an SI of three, whereas the gradient data have an SI of four. The developed extended Euler deconvolution method based on the Hilbert transform provides a reliable means for calculating the spatial location, depth, and SI of compact and isolated anomalies; it has enabled us to perform automatic anomaly selection for further analysis. Our method first examines the anomaly decay and selects possible UXO anomalies based on the expected SI. We refine the result further by post-Euler amplitude analysis using the relative source strength of the anomalies selected in the first stage. The amplitude analysis statistically identifies weak anomalies that are due to noise in the data. This enhances the final result and eliminates automatic picks that fall within the noise level. We have demonstrated the effectiveness of the method using synthetic and field data sets.

Neural Network Aided Adaptive Filtering and Smoothing for an Integrated INS/GPS Unexploded Ordnance Geolocation System

The precise geolocation of buried unexploded ordnance (UXO) is a significant component of the detection, characterization, and remediation process. Traditional geolocation methods associated with these procedures are inefficient in helping to distinguish buried UXO from relatively harmless geologic magnetic sources or anthropic clutter items such as exploded ordnance fragments and agricultural or industrial artefacts. The integrated INS/GPS geolocation system can satisfy both high spatial resolution and robust, uninterrupted positioning requirements for successful UXO detection and characterization. To maximize the benefits from this integration, non-linear filtering strategies (such as the unscented Kalman filter) have been developed and tested using laboratory data. In addition, adaptive filters and smoothers have been designed to address variable or inaccuratea prioriknowledge of the process noise of the system during periods of GPS unavailability. In this paper, we study and compare the improvement in the geolocation accuracy when the neural network approach is applied to aid the adaptive versions of the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). The test results show that the neural network based filters can improve overall position accuracy and can homogenize the performance of the integrated system over a range of relatively quiet to dynamic environments. Navigation-grade and medium-grade IMUs were compared and, with standard smoothing applied to the new filters, geolocation accuracy of 5 cm (13 cm) was achieved with the navigation- (medium-) grade unit within 8-second intervals that lack external control, which is at or close to the area-mapping accuracy requirement for UXO detection.