Journal articles: 'UXO'

1

Kappler, K. N., and E. Gasperikova. "A Hybrid Method for UXO vs. Non-UXO Discrimination." Journal of Environmental & Engineering Geophysics 16, no. 4 (December 1, 2011): 177–89. http://dx.doi.org/10.2113/jeeg16.4.177.

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Butler, Dwain K. "Landmines and UXO." Leading Edge 16, no. 10 (October 1997): 1460. http://dx.doi.org/10.1190/1.1437514.

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Stanbridge, Andrew. "UXO in Laos." Anthropology Now 3, no. 2 (September 2011): 48–61. http://dx.doi.org/10.1080/19492901.2011.11728321.

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4

Kay, Simon. "UXO? MM? QED." British Journal of Plastic Surgery 58, no. 2 (March 2005): 145–46. http://dx.doi.org/10.1016/j.bjps.2005.01.001.

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Hameed, Qabas A., Harith A. Hussein, Mohamed A. Ahmed, Mahmood M. Salih, Reem D. Ismael, and Mohammed Basim Omar. "UXO-AID: A New UXO Classification Application Based on Augmented Reality to Assist Deminers." Computers 11, no. 8 (August 19, 2022): 124. http://dx.doi.org/10.3390/computers11080124.

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Unexploded ordnance (UXO) is a worldwide problem and a long-term hazard because of its ability to harm humanity by remaining active and destructive decades after a conflict has concluded. In addition, the current UXO clearance methods mainly involve manual clearance and depend on the deminer’s experience. However, this approach has a high misclassification rate, which increases the likelihood of an explosion ending the deminer’s life. This study proposes a new approach to identifying the UXO based on augmented reality technology. The methodology is presented based on two phases. Firstly, a new dataset of UXO samples is created by printing 3D samples and building a 3D model of the object data file with accurate data for 3D printed samples. Secondly, the development of the UXO-AID mobile application prototype, which is based on augmented reality technology, is provided. The proposed prototype was evaluated and tested with different methods. The prototype’s performance was measured at different light intensities and distances for testing. The testing results revealed that the application could successfully perform in excellent and moderate lighting with a distance of 10 to 30 cm. As for recognition accuracy, the overall recognition success rate of reached 82.5%, as the disparity in the number of features of each object affected the accuracy of object recognition. Additionally, the application’s ability to support deminers was assessed through a usability questionnaire submitted by 20 deminers. The questionnaire was based on three factors: satisfaction, effectiveness, and efficiency. The proposed UXO-AID mobile application prototype supports deminers to classify the UXO accurately and in real time, reducing the cognitive load of complex tasks. UXO-AID is simple to use, requires no prior training, and takes advantage of the wide availability of mobile devices.

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Bowers, R. Josh, and Beatrice A. Bidwell. "Geophysics and UXO detection." Leading Edge 18, no. 12 (December 1999): 1389–91. http://dx.doi.org/10.1190/1.1438224.

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Huang, Haoping, Bill SanFilipo, and I. J. Won. "Optimizing decision threshold and weighting parameter for UXO discrimination." GEOPHYSICS 71, no. 6 (November 2006): G313—G320. http://dx.doi.org/10.1190/1.2353802.

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Establishing a decision threshold to separate unexploded ordnance (UXO) from clutter is a critical task in UXO discrimination procedures. It is, however, a difficult task because the decision threshold depends on many parameters such as local geology, distribution of UXO and clutter, and cultural and environmental noise at a given UXO cleanup site. Some discrimination algorithms also use site-dependent weighting factors. In practice, one determines these parameters empirically from calibration experiments. To facilitate this task, we introduce a simple function called the degree of discrimination, constructed from calibration plots at a UXO cleanup site. First, we compute the degree of discrimination for a representative set of thresholds and weighting factors using ground truth data from the calibration site. Then, we find the optimum decision threshold and weighting factors associated with the best degree of discrimination. Finally, we use these optimal parameters for the UXO site cleanup. We have conducted two experiments using the broadband electromagnetic (EM) sensor with a concentric coil configuration. Our experiments show that 92% of UXO is declared and 74% of clutter is rejected using our optimized threshold and weights. A blind test shows that optimizing the threshold and weights increases the degree of discrimination from 0 to 0.15. Our tests also show that the detection scheme with a collective threshold for all UXO types is easier to use and yields better discrimination than the scheme based on individual thresholds for each UXO type.

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Potić, Ivan, Nenad Komazec, Ljiljana Mihajlović, Aleksandar Milić, and Saša Bakrač. "Risk management of unexploded ordnance in the Republic of Serbia for environmental protection: Borovac case study." Vojnotehnicki glasnik 71, no. 4 (2023): 1087–114. http://dx.doi.org/10.5937/vojtehg71-44656.

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Introduction/purpose: Decades of dealing with unexploded ordnance (UXO) in some areas of the Republic of Serbia have confirmed that it presents a substantial hazard to the security of people, property, and the environment. Even though the terrain has been cleaned, various threats from difficult-tofind UXO components remain serious. Inadequate systemic solutions for UXO management can have significant harmful consequences. Methods: Based on the spatial distribution analysis and different UXO types and quantities, this article studies the effects of dangerous components of unexploded ordnance on human lives and the environment. Two different geospatial analyses were performed including the guidelines for risk management through risk elimination based on multiple criteria, the GIS, and the Remote Sensing analysis. Results: Two different geospatial analyses resulted in the areas at high risk of remaining UXO. Conclusion: The article significantly contributes to creating an environmental risk management strategy for UXO-contaminated regions. It presents an effective technique for addressing risk assessment challenges in such sites. The analysis considers both risk analysis and environmental protection options. Using the multi-criteria analysis and the GIS, it estimates the exposure of built structures, people, soil types, and plant species to UXO dangers in key locations. This paper serves as a guideline for environmental risk assessment.

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Brighouse, Jack, Martin Wood, Eoin McGregor, Andrew Kirkland, David Sinclair, Dorthe Reng Erbs-Hansen, and Simon Hviid. "Inverse modelling and classification of magnetic responses to improve marine unexploded ordnance rationalization." Geophysical Journal International 237, no. 1 (February 2, 2024): 123–44. http://dx.doi.org/10.1093/gji/ggad490.

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SUMMARY Unexploded ordnance (UXO), often deployed in WWI and WWII, are still present on the seabed posing a risk to seabed construction. UXO surveys identify potential UXO targets which are then investigated and removed where necessary; however, approximately 96 per cent of targets investigated on projects included in this study were non-UXO (false positives). Here we investigate methods of improving statistical confidence in targets picked through the improved classification of magnetic response, utilizing simulation methods and historic data. A simulation of the induced magnetism of UXO was developed to model the most likely dimensions and orientation of a given source item. Modelling results and measured variables were combined in an optimization algorithm, hereon referred to as ‘the classifier’. We document the results of integrating the magnetic responses of 3027 targets from 18 offshore wind projects into the classifier. Five of these projects were performed as tests in which the target results were unknown during classification. Finally, the classifier was deployed on a live project, Hollandse Kust Zuid 3 and 4 Offshore Wind Farm, in which it enabled the removal of 67 targets from the from the 1200-target investigation list. The classifier proved to be a valuable additional tool to assist the target rationalization process, reliably and repeatably distinguishing UXO from other items, thereby reducing false positives and repeatably demonstrating no threshold UXO false negatives. Assumptions and limitations of this methodology were highlighted, which must be understood and considered when integrating this approach on future projects.

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Wigh, Mark David, Thomas Mejer Hansen, and Arne Døssing. "Inference of unexploded ordnance (UXO) by probabilistic inversion of magnetic data." Geophysical Journal International 220, no. 1 (October 19, 2019): 37–58. http://dx.doi.org/10.1093/gji/ggz421.

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SUMMARY Magnetic modelling of unexploded ordnance (UXO) is a well-documented method used to interpret magnetic anomalies occurring in UXO excavation surveys. By treating UXO as a ferrous spheroidal object, the induced dipole moment can be estimated by approximation of UXO characteristics such as shape, size and orientation. Inversion of magnetic data with respect to UXO requires one to solve the equation for the induced dipole moment, while also determining the location and orientation of the object. This is a highly nonlinear, non-unique problem, where many solutions often are present, which make it difficult for standard inversion methods, such as linearized approaches and maximum likelihood estimators, in assessing uncertainties and correlations in estimated model parameters that often result in an incomplete solution. In this study, we treat the problem concerning magnetic UXO inversion by a probabilistic approach using Markov chain Monte Carlo (McMC) sampling. To deal with the potential multimodality, a combination of two well-known McMC sampling methods is employed in a single-chain approach: the extended Metropolis algorithm is used for efficient local sampling, and the Gibbs sampler is used to help exploring the possible multimodal density of the posterior. By adding a Gibbs step we significantly increase the efficiency of the extended Metropolis, making it viable to use as a single-chain sampler for this problem. We refer to the algorithm as the Gibbs-within-Metropolis algorithm. We test and compare the proposed algorithm to a multichain McMC parallel tempering setup using the extended Metropolis algorithm. We then present synthetic cases and a real data case, where the algorithm is used. We demonstrate how the probabilistic approach allows full inference of the parameters describing a UXO while also including the possible presence of remanent magnetization.

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Gamey, T. J. "Magnetic Response of Clustered UXO Targets." Journal of Environmental & Engineering Geophysics 13, no. 3 (September 1, 2008): 211–21. http://dx.doi.org/10.2113/jeeg13.3.211.

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12

Daily, William, Abelardo Ramirez, Robin Newmark, and Victor George. "Imaging UXO Using Electrical Impedance Tomography." Journal of Environmental and Engineering Geophysics 5, no. 4 (December 2000): 11–23. http://dx.doi.org/10.4133/jeeg5.4.11.

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13

Constantinoiu, Laurențiu-Florin, Eugen Rusu, and Maria-Emanuela Mihailov. "UXO Assessment on the Romanian Black Sea Coast." Journal of Marine Science 4, no. 2 (June 13, 2022): 7. http://dx.doi.org/10.30564/jms.v4i2.4497.

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This paper aims to provide the reader with the results of the Unexploded Ordnance (UXO) survey of the defensive historical naval minefields launched by the Romanian and German Navies on the Romanian Black Sea coast, during the Second World War. This UXO survey was carried out between 2015-2018 by the Romanian Navy’s hydrographic ship “Commander Alexandru Cătuneanu” and Romanian Mine Warfare Data Center, using towed side-scan sonar technology and oceanographic observations. After explaining the materials and methodology, the results are presented and discussed: mosaics of the minefields, side-scan images of UXO contacts, side-scan images of the wrecks that were sunk in the minefields and some visible natural geological features of the seafloor. It was concluded that most of the objects discovered are sinkers, wreck debris or parts of chains, which does not represent a danger to navigation.

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Gasperikova, Erika, J. Torquil Smith, H. Frank Morrison, Alex Becker, and Karl Kappler. "UXO detection and identification based on intrinsic target polarizabilities — A case history." GEOPHYSICS 74, no. 1 (January 2009): B1—B8. http://dx.doi.org/10.1190/1.2997419.

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Electromagnetic induction data parameterized in time-dependent object intrinsic polarizabilities can discriminate unexploded ordnance (UXO) from false targets (scrap metal). Data from a cart-mounted system designed to discriminate UXO of [Formula: see text] in diameter are used. Discriminating UXO from irregular scrap metal is based on the principal dipole polarizabilities of a target. Nearly intact UXO displays a single major polarizability coincident with the long axis of the object and two equal, smaller transverse polarizabilities, whereas metal scraps have distinct polarizability signatures that rarely mimic those of elongated symmetric bodies. Based on a training data set of known targets, objects were identified by estimating the probability that an object is a single UXO. Our test survey took place on a military base where [Formula: see text] mortar shells and scrap metal were present. We detected and correctly discriminated all [Formula: see text] mortars, and in that process we added 7% and 17%, respectively, of dry holes (digging scrap) to the total number of excavations in two different survey modes. We also demonstrated a mode of operation that might be more cost effective than current practice.

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Rancich, Tom. "Search and Recovery of Munitions by Divers." Marine Technology Society Journal 45, no. 6 (November 1, 2011): 75–79. http://dx.doi.org/10.4031/mtsj.45.6.9.

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AbstractThe trend in the United States is to treat the underwater unexploded ordnance (UXO) problem the same as the land problem. This is fundamentally flawed. Not only must underwater sites be treated differently than land sites, but each underwater site must be treated differently, bringing to bear all possible solutions to develop the best course(s) of action. Although many sites will have similar assets applied to the solution, there will be no cookie-cutter solution. Because of the dynamic nature of the underwater environment, an underwater UXO operation is distinctly unique from a land operation. As the environment is dynamic, so must the solution be. Flexibility in planning and execution of the production operation is a necessity in underwater UXO activities. That fact requires a different type of work force; one trained and encouraged to innovate and keen to be involved in the planning process. The problem facing the underwater ordnance industry is a production problem: achieving production that must be safe, efficient, cost effective, and beneficial. The underwater UXO industry is heavily populated with experts in tactical operations involving defense explosives, i.e., mines, in military operations. That expertise must be balanced with professionals with production experience. This article will compile, analyze, and compare years of successful experience in underwater operations and UXO removal. At the conclusion, readers will have a better understanding of problems encountered throughout the planning and execution of underwater UXO removal actions and subsequent solutions.

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Han, Songtong, Xiaoli Rong, Leixiang Bian, Mingyou Zhong, and Lining Zhang. "The Application of Magnetometers and Electromagnetic Induction Sensors in UXO Detection." E3S Web of Conferences 131 (2019): 01045. http://dx.doi.org/10.1051/e3sconf/201913101045.

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This paper introduces the physical model of unexploded ordnance (UXO) in the magnetization process and the formula derivation of the magnetic dipole model. The application of magnetometers and electromagnetic induction sensors in the detection of UXO is introduced. The magnetometers introduce the total field measurements technology of the CS optical-pump marine magnetometer and the MagSTAR (Magnetic Scalar Triangulation and Ranging) gradient detection technology. The electromagnetic induction sensors introduce the working theories and the popular product models of Geophex company and Geonics Ltd. The method of detecting UXO by MTADS of United States Naval Research Laboratory (The multisensor towed array detection system) compares the difference between the United States Naval Research Laboratory for target recognition.

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Davis, Kristofer, Yaoguo Li, and Misac Nabighian. "Automatic detection of UXO magnetic anomalies using extended Euler deconvolution." GEOPHYSICS 75, no. 3 (May 2010): G13—G20. http://dx.doi.org/10.1190/1.3375235.

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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.

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Mendonça, Luís Felipe, Jorge Arigony-Neto, Claudio Mendes Junior, Virginia Santos, and Ricardo Jaña. "ESTIMATIVA DAS VARIAÇÕES SAZONAIS NO FLUXO DA GELEIRA GREY, PATAGÔNIA, POR IMAGENS SAR." Revista Brasileira de Cartografia 67, no. 7 (June 17, 2019): 1541–55. http://dx.doi.org/10.14393/rbcv67n7-49197.

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Este trabalho apresenta estimativas da velocidade de fl uxo da geleira Grey, localizada no Campo de Gelo PatagônicoSul, para o período de outubro de 2011 e janeiro a abril de 2012. Obtidos através de um algoritmo baseado no cálculode correlação cruzada entre pares de imagens SAR COSMO-SkyMed, os valores de velocidade foram posteriormenteinterpolados, de forma a gerar superfícies contínuas que ilustrem a direção e intensidade de fl uxo da geleira. Os resultados foram comparados com dados meteorológicos, disponibilizados pelo Serviço Meteorológico Argentino, parainterpretar o padrão sazonal na velocidade de deslocamento. Outubro e abril registraram valores médios de velocidadede fl uxo de 1,2 ± 0,6 md-1e 1,1 ± 0,5 md-1, respectivamente. Durante o período de verão, os meses de janeiro, fevereiroe março apresentaram valores de velocidade de fl uxo de 1,5 ± 0,7 md-1; 1,3 ± 0,6 md-1 e 1,4 ± 0,7 md-1 variando diretamente com a temperatura média mensal. Com um coefi ciente de correlação estimado em 0,96; os resultados indicamque os valores mensais do fl uxo da geleira Grey possuem uma relação positiva com a temperatura do ar na superfície.A técnica desenvolvida, a partir do algoritmo correlCorresp aplicada em ambiente MATLAB, permitiu uma análiseaprimorada das variações na velocidade superfi cial de geleiras nas mais distintas escalas temporal e espacial.

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Grezmak, John, and Kathryn A. Daltorio. "Probing with Each Step: How a Walking Crab-like Robot Classifies Buried Cylinders in Sand with Hall-Effect Sensors." Sensors 24, no. 5 (February 29, 2024): 1579. http://dx.doi.org/10.3390/s24051579.

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Shallow underwater environments around the world are contaminated with unexploded ordnances (UXOs). Current state-of-the-art methods for UXO detection and localization use remote sensing systems. Furthermore, human divers are often tasked with confirming UXO existence and retrieval which poses health and safety hazards. In this paper, we describe the application of a crab robot with leg-embedded Hall effect-based sensors to detect and distinguish between UXOs and non-magnetic objects partially buried in sand. The sensors consist of Hall-effect magnetometers and permanent magnets embedded in load bearing compliant segments. The magnetometers are sensitive to magnetic objects in close proximity to the legs and their movement relative to embedded magnets, allowing for both proximity and force-related feedback in dynamically obtained measurements. A dataset of three-axis measurements is collected as the robot steps near and over different UXOs and UXO-like objects, and a convolutional neural network is trained on time domain inputs and evaluated by 5-fold cross validation. Additionally, we propose a novel method for interpreting the importance of measurements in the time domain for the trained classifier. The results demonstrate the potential for accurate and efficient UXO and non-UXO discrimination in the field.

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Son, Derac. "Magnertic Methods to Detect Mines and UXO." Journal of the Korean Magnetics Society 30, no. 3 (June 30, 2020): 106–13. http://dx.doi.org/10.4283/jkms.2020.30.3.106.

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Arcone, Steven, David Finnegan, and Ginger Boitnott. "GPR characterization of a lacustrine UXO site." GEOPHYSICS 75, no. 4 (July 2010): WA221—WA239. http://dx.doi.org/10.1190/1.3467782.

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We used [Formula: see text] ground-penetrating-radar (GPR) reflection profiles to determine if high-explosive (HE) depth bombs were possibly detonated within a small New England lake formerly used as a bombing range, as well as the depths and distribution of inert and possibly unexploded ordnance (UXO) within the subbottom sediments. Maximum water depth was [Formula: see text]. The primary munitions were unarmed practice bombs, but terrestrial fragments from HE depth bombs led us to seek stratigraphic obliteration and distortion as evidence of their use. The low water conductivity and quartz-rich sediments provided more than [Formula: see text] of subbottom penetration beneath slope and shelf sediments. The high permittivities of the water and subbottom sediments provided good antenna directivity, excellent 2D migrations, multicentimeter vertical resolution, and a unique pulse waveform signature for metal objects. Our line profiles revealed hundreds of subbottom diffractions, which implied an areal distribution of thou-sands of suspicious objects. Most lay beneath the central basin, but many resided beneath the slopes and shelves as well. Supplementary profiles of a nearby pristine lake and of controlled munitions, a side-scan sonar bottom survey, and time-domain reflectometry dielectric measurements of sediment samples corroborated our findings of natural stratigraphy, a unique metallic diffraction phase signature, the existence of many nonmetallic objects including logs, and subbottom relative permittivities ranging from 28 to 76. The intact natural lacustrine strata, including deltaic foresets and bottom sets, faults, and conformable and unconformable horizons, suggest that live bombs likely did not detonate in the lake. The only stratigraphic disturbances we found were apparent perforations beneath about [Formula: see text] of water, within which diffractions of metallic origin originated. The dielectric results and the prominent slope strata over the deepest horizons led us to conclude that the exceptional subbottom penetration existed under predominantly sandy sediments.

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Paoletti, V., A. Buggi, and R. Pašteka. "UXO Detection by Multiscale Potential Field Methods." Pure and Applied Geophysics 176, no. 10 (May 3, 2019): 4363–81. http://dx.doi.org/10.1007/s00024-019-02202-7.

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Kolster, Mick Emil, and Arne Døssing. "Scalar magnetic difference inversion applied to UAV-based UXO detection." Geophysical Journal International 224, no. 1 (October 8, 2020): 468–86. http://dx.doi.org/10.1093/gji/ggaa483.

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SUMMARY During scalar magnetic surveys, where the amplitude of the magnetic field is measured, small changes in towed sensor positions can produce complex noise-resembling signals in the data. For well-constructed measurement systems, these signals often contain valuable information, rather than noise, but it can difficult to realize their potential. We present a simple, general approach, which can be used to directly invert data from scalar magnetic surveys, regardless of dynamic or unexpected sensor position variations. The approach generalizes classic along-track gradients to an iterative, or recursive, difference, that can be applied irrespective of the amount of magnetic sensors and their positions within a dynamic measurement system, as long as these are known. The computed difference can be inverted directly, providing a versatile method with very little data pre-processing requirements, which we denote as recursive difference inversion. We explain the approach in a general setting, and expand it to provide a complete framework for Unexploded Ordnance (UXO) detection using a point-dipole model. Being an extension of classic along-track gradients, the method retains many of the same properties, which include added robustness to external time-dependent disturbances, and the ability to produce aesthetic visual data representations. In addition, the framework requires neither tie lines, data levelling, nor diurnal corrections. Only light pre-processing actions, namely initial survey trimming and data position calculation, are required. The method is demonstrated on data from a dual sensor system, conventionally referred to as a vertical gradiometer, which is towed from an Unmanned Aerial Vehicle. The system enables collection of high-quality magnetic data in adverse settings, and simultaneously reduces the risk of inadvertent UXO detonations. To enable qualitative testing, we established a UXO detection test facility with several buried UXO, typical to World War II, in a magnetically complex in-land area. Data from the test facility was mainly used to evaluate inversion robustness and depth accuracy of the point-dipole model. Subsequently, we apply the method to real UXO survey data collected for the Hornsea II offshore wind farm project in the United Kingdom. This data set was collected in a coastal setting, and subject to significant sensor position changes during flight due to varying wind conditions over multiple survey days. This makes the raw data set challenging to interpret directly, but it can still be easily and reliably inverted for source locations through recursive difference inversion. In each of the two data sets, we attempt to recover UXO positions using recursive difference inversion on data from both a single sensor, as well as on data from two synchronized sensors, in each case inverting the difference directly for point-dipole model parameters. To seed the inversion, we propose a simple routine for picking out potential targets, based on the choice of a significant peak prominence in the time-series of computed differences. Higher order difference inversion was found to provide robust results in the magnetically complex setting, and the recovered equivalent dipole depths were found to approximate the actual UXO depths well.

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Brown, Daniel C., Scott Brumbaugh, Mark Fanton, Richard Meyer, Shawn Johnson, and Cale Brownstead. "Projector design for imaging of buried unexploded ordnance." Journal of the Acoustical Society of America 151, no. 4 (April 2022): A57. http://dx.doi.org/10.1121/10.0010646.

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Recent modeling and field experimentation has shown very-shallow-water acoustic imaging of buried unexploded ordnance (UXO) can place stringent requirements on the sonar transmit system. Achieving high-resolution imagery requires large transmit bandwidth. Imaging deeply buried UXO requires low operating frequencies and high source levels to overcome sediment attenuation. Imaging UXO near the sediment–water interface requires short transmit waveforms that require projectors with a low mechanical quality factor for accurate reproduction. This work presents the results of a recent design study, device fabrication, and acoustic testing of a new projector intended for operation as part of a buried UXO imaging system. The analysis will focus on the design and material selection of the head mass and the ring stack used in the tonpilz device. The head mass design trade considered construction from aluminum or an aluminum beryllium metal matrix composite (AlBeMet). The ring stack design trade considered traditional polycrystalline lead zirconate titanate (PZT), ternary single crystal lead indium niobium–lead indium manganese niobium titanate (PIN-PMN-PT), and textured manganese doped lead magnesium niobate–lead zirconate titanate (Mn-PMN-PZT). Finite element simulations and measured results will be presented.

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Lee, Jong Ki, and Christopher Jekeli. "Rao-Blackwellized Unscented Particle Filter for a Handheld Unexploded Ordnance Geolocation System using IMU/GPS." Journal of Navigation 64, no. 2 (March 2, 2011): 327–40. http://dx.doi.org/10.1017/s0373463310000548.

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The existence of Unexploded Ordnance (UXO) is a serious environmental hazard, especially in areas being converted from military to civilian use. The detection and discrimination performance of UXO detectors depends on the sensor technology as well as on the processing methodology that inverts the data to infer UXO. The detection systems, typically electro-magnetic induction (EMI) devices, require very accurate positioning (or geolocation) in order to discriminate candidate UXO from non-hazardous items. For this paper, a hand-held geolocation system based on a tactical-grade IMU, such as the HG1900, was tested in the laboratory over a small, metre-square area in sweep and swing modes. A camera position system was used to emulate GPS or alternative ground-based external ranging systems that control positioning errors. The proposed integration algorithm is a combination of linear filtering (Extended Kalman Filter) and nonlinear, also non-Gaussian filtering (Unscented Particle Filter) in the form of the Rao-Blackwellized Particle Filter (RBPF). The test results show that the position accuracy was improved by applying nonlinear filter-based smoothing techniques in both the straight and curved sections of the sweep and swing trajectories.

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Beran, Laurens, Barry Zelt, Leonard Pasion, Stephen Billings, Kevin Kingdon, Nicolas Lhomme, Lin-Ping Song, and Doug Oldenburg. "Practical strategies for classification of unexploded ordnance." GEOPHYSICS 78, no. 1 (January 1, 2013): E41—E46. http://dx.doi.org/10.1190/geo2012-0236.1.

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We have developed practical strategies for discriminating between buried unexploded ordnance (UXO) and metallic clutter. These methods are applicable to time-domain electromagnetic data acquired with multistatic, multicomponent sensors designed for UXO classification. Each detected target is characterized by dipole polarizabilities estimated via inversion of the observed sensor data. The polarizabilities are intrinsic target features and so are used to distinguish between UXO and clutter. We tested this processing with four data sets from recent field demonstrations, with each data set characterized by metrics of data and model quality. We then developed techniques for building a representative training data set and determined how the variable quality of estimated features affects overall classification performance. Finally, we devised a technique to optimize classification performance by adapting features during target prioritization.

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Cristaudo, Demetra, Benedict M. Gross, and Jack A. Puleo. "Momentum Balance Analysis of Spherical Objects and Long-Term Field Observations of Unexploded Ordnance (UXO) in the Swash Zone." Journal of Marine Science and Engineering 11, no. 1 (January 3, 2023): 79. http://dx.doi.org/10.3390/jmse11010079.

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Military activity has resulted in unexploded ordnance (UXO) existing in the nearshore. Understanding and predicting UXO behavior is important for object identification, and management. Here, two studies (laboratory and fieldwork) have been conducted to observe UXO surrogates in the swash zone and relate burial and migration to the underlying forcing conditions. A small-scale laboratory dam-break study was conducted to quantify migration of varying density spherical objects at different locations on a sloping, mobile, sandy bed. A moment balance was applied to derive two data-driven relationships to: (1) predict moments from the cross-shore flow velocity with predictions confined within a factor of two; (2) predict upslope or downslope migration from the moment. Fitting coefficients for the upslope and downslope relationships vary as a function of density, initial position, and burial. A field study was also conducted to investigate long-term behavior of eight varieties of UXO surrogates. Of the 129 observations, 56% were mobilized of which 76% were directed offshore. Burial/exposure was mostly related to far-field beach accretion/erosion (67%). However, scouring processes were also observed. Data showed that migration is likely a short-term process and most munitions will ultimately scour into a mobile bed.

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Llopis, J. L. "Introduction to This UXO Special Issue of JEEG." Journal of Environmental & Engineering Geophysics 13, no. 3 (September 1, 2008): v—vi. http://dx.doi.org/10.2113/jeeg13.3.fmv.

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Weichman, Peter B. "Validation of Advanced EM Models for UXO Discrimination." IEEE Transactions on Geoscience and Remote Sensing 51, no. 7 (July 2013): 3954–67. http://dx.doi.org/10.1109/tgrs.2012.2227490.

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Zhang, Qing, Waleed Al-Nuaimy, and Yi Huang. "Detection of Deeply Buried UXO Using CPT Magnetometers." IEEE Transactions on Geoscience and Remote Sensing 45, no. 2 (February 2007): 410–17. http://dx.doi.org/10.1109/tgrs.2006.886178.

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Bray, Matthew P., and Curtis A. Link. "Learning Machine Identification of Ferromagnetic UXO Using Magnetometry." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8, no. 2 (February 2015): 835–44. http://dx.doi.org/10.1109/jstars.2014.2362920.

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McKenna, Sean A., and Brent Pulsipher. "Quantifying and reducing uncertainty in UXO site characterization." Stochastic Environmental Research and Risk Assessment 23, no. 2 (January 16, 2008): 153–54. http://dx.doi.org/10.1007/s00477-007-0203-5.

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McKenna, Sean A. "UXO target area identification with hidden Markov models." Stochastic Environmental Research and Risk Assessment 23, no. 2 (January 16, 2008): 193–202. http://dx.doi.org/10.1007/s00477-007-0209-z.

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Nelson, H. H., and J. R. McDonald. "Multisensor towed array detection system for UXO detection." IEEE Transactions on Geoscience and Remote Sensing 39, no. 6 (June 2001): 1139–45. http://dx.doi.org/10.1109/36.927427.

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Ibraheem, Ismael M., Hasan Aladad, Mohamad Faek Alnaser, and Randell Stephenson. "IAS: A New Novel Phase-Based Filter for Detection of Unexploded Ordnances." Remote Sensing 13, no. 21 (October 28, 2021): 4345. http://dx.doi.org/10.3390/rs13214345.

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A new phase-based filter (called improved analytical signal (IAS)) is introduced to detect buried unexploded ordnance (UXO) precisely from magnetic fields using the arcsine function of the ratio of the first-order vertical derivative of the analytical signal to the first-order derivatives of the x-, y-, and z-components of the analytical signal. The calculations are computed in the frequency domain and then transformed back into the space domain using the inverse Fourier transform. The filter has been tested on magnetic data collected at a test site with UXO bodies of variable orientation. It was also validated on magnetic data measured at a former army artillery range in Slovakia. The results show that the IAS filter not only revealed better imaging of the UXO bodies compared to the other commonly used filters but also produced a high-resolution image with much less influence of noise.

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Hussein, Harith A., Qabas A. Hameed, Reem D. Ismael, Mustafa Zuhaer Nayef Al-Dabagh, and Moudher Khalid Abdalhammed. "Applying Web Augmented Reality to Unexplosive Ordnance Risk Education." Computers 12, no. 2 (February 1, 2023): 31. http://dx.doi.org/10.3390/computers12020031.

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Unexploded Ordnances (UXOs) are considered a global concern and a persistent hazard due to their capability to endanger civilians and the place where they are located, and the probability of remaining active explosives even after decades of ending a conflict. Hence, risk education is crucial for providing individuals with life-saving knowledge on recognizing, avoiding, and reporting UXO threats. The main objective of this study is to develop a web augmented reality (AR) application to investigate the effect of WAR on non-explosive ordnance risk education. Firstly, UXO 3D models are edited and constructed using the Blender 3D computer graphics software. Secondly, the proposed web AR application is developed using MindAR JavaScript-based library. Finally, the web application QR code and UXO Hiro codes are printed on infographics and brochures to be distributed to secondary school students aged 12 to 18 at six public and private schools in Tikrit City, Salah al-Din governorate, Iraq. Survey questions are validated and distributed to be collected from 137 respondents. The present study shows that the proposed web AR application increased respondents’ information in identifying UXO by 54.7%. Approximately 70% of respondents use the Internet for more than 3 h daily. Institutions should use new risk education methods in line with the tremendous technological growth and invest students’ knowledge and time in this field. Better risk education teaching methods can save lives.

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Theera-Umpon, Nipon. "Unexploded Ordnance Detection Using Region of Interest in Range Domain of Ground Penetrating Radar." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 10 (December 20, 2007): 1184–88. http://dx.doi.org/10.20965/jaciii.2007.p1184.

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Buried unexploded ordnance (UXO) and land mines are grave threats to civilians who go back to contaminated areas in the postwar period. In this research, we propose a new technique to detect UXOs from ground penetrating radar (GPR) signals. The technique is based on an energy-based feature of the region of interest (ROI). A ROI selection technique in range domain is also proposed. The proposed method was tested with the UXO data collected by Battelle company and the Ohio State University. This data set was made available to public through the Unexploded Ordnance Center of Excellence (UXOCOE), Department of Defense, U.S.A. The results evaluated in terms of Receiver Operating Characteristic (ROC) curves suggest that our proposed technique performs very well. Comparisons to a traditional detection technique and our previously proposed technique are conducted. The improvement by the proposed technique does not only speed up the UXO/land mine clearance operation, but also save operating cost.

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Billings, Stephen, and Laurens Beran. "Optimizing electromagnetic sensors for unexploded ordnance detection." GEOPHYSICS 82, no. 3 (May 1, 2017): EN25—EN31. http://dx.doi.org/10.1190/geo2016-0232.1.

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Time-domain electromagnetic (TEM) instruments are the predominant geophysical sensor for detection of buried unexploded ordnance (UXO). Detection surveys commonly use towed TEM sensor arrays to acquire a digital map for target detection. We use a dipolar model to predict a detection threshold for a UXO at a specified clearance depth, given an arbitrary sensor geometry. In general, the minimum target response is obtained for a horizontally oriented target. We find that for multistatic sensors, the minimum response can also depend on the azimuth of the target. By considering the statistics of the target response, we find that the detection threshold can be raised slightly while still ensuring a high probability of detection of UXO at depth. This increase in the detection threshold can have a significant effect on the number of false alarms that need to be interrogated or investigated and hence on the cost of clearance. We also use Monte Carlo simulation to investigate how array geometry and height affect clutter rejection.

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Blachnik, Marcin, Roman Przyłucki, Sławomir Golak, Piotr Ściegienka, and Tadeusz Wieczorek. "On the Development of a Digital Twin for Underwater UXO Detection Using Magnetometer-Based Data in Application for the Training Set Generation for Machine Learning Models." Sensors 23, no. 15 (July 30, 2023): 6806. http://dx.doi.org/10.3390/s23156806.

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Scanning underwater areas using magnetometers in search of unexploded ordnance is a difficult challenge, where machine learning methods can find a significant application. However, this requires the creation of a dataset enabling the training of prediction models. Such a task is difficult and costly due to the limited availability of relevant data. To address this challenge in the article, we propose the use of numerical modeling to solve this task. The conducted experiments allow us to conclude that it is possible to obtain high compliance with the numerical model based on the finite element method with the results of physical tests. Additionally, the paper discusses the methodology of simplifying the computational model, allowing for an almost three times reduction in the calculation time without affecting model quality. The article also presents and discusses the methodology for generating a dataset for the discrimination of UXO/non-UXO objects. According to that methodology, a dataset is generated and described in detail including assumptions on objects considered as UXO and nonUXO.

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Ki Lee, Jong, and Christopher Jekeli. "Neural Network Aided Adaptive Filtering and Smoothing for an Integrated INS/GPS Unexploded Ordnance Geolocation System." Journal of Navigation 63, no. 2 (February 23, 2010): 251–67. http://dx.doi.org/10.1017/s0373463309990397.

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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 inaccurate a priori knowledge 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.

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Da Silva, Suzy Cristina Pedroza, and Gustavo Macedo de Mello Baptista. "MODELAGENS DE SEQUESTRO FLORESTAL DE CARBONO E DOS CONTEÚDOS DE CO2 ATMOSFÉRICO COM DADOS HYPERION EM DIFERENTES AMBIENTES NA AMAZÔNIA BRASILEIRA." Revista Brasileira de Cartografia 67, no. 7 (June 17, 2019): 1509–21. http://dx.doi.org/10.14393/rbcv67n7-49195.

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Esse estudo analisou a concentração e o fl uxo de dióxido de carbono das torres micrometeorológicas pelo modelo desequestro fl orestal de carbono denominado de CO2fl ux, validando essa modelagem pelo índice ICO2, em diferentespaisagens na Amazônia. No estudo foram utilizadas 21 imagens hiperespectrais, obtidas pelo sensor Hyperion/EO-1que opera com 242 bandas espectrais nos comprimentos de onda de 0,4 a 2,5 µm, com uma resolução espacial de 30metros. O CO2fl ux mede a efi ciência do processo de sequestro de carbono pela vegetação. Para sua determinação, aintegração de dois índices de vegetação, i.e., o NDVI com o sPRI. O ICO2 é determinado pela intensidade da feição deabsorção do gás centrada em 2,0 µm. Os resultados fazem referência as relações estatísticas entre as informações obtidascom a aplicação do modelo CO2fl ux e as informações de campo da concentração (ppm) e fl uxo (mol.m-2.s-1) de CO2 eindicam que o CO2fl ux pode ser utilizado tanto com dados de concentração, quanto com dados de fl uxo. Os melhoresajustes para o CO2fl ux pontual foram apresentados para a associação com dados de fl uxo (mol.m-2.s-1), enquanto que,para as análises a partir do footprint, melhores resultados foram verifi cados para a associação entre os dados espectraise as medidas de concentração de CO2 (ppm) no topo da torre. Como conclusão, o índice ICO2 mostrou-se efi ciente navalidação do modelo de sequestro fl orestal de carbono para os ambientes naturais e antrópicos apresentando correlaçõescom os dados das torres instaladas na Amazônia Brasileira.

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Holladay, J. S., W. E. Doll, L. P. Beard, J. L. C. Lee, and D. T. Bell. "UXO Time-Constant Estimation from Helicopter-Borne TEM Data." Journal of Environmental & Engineering Geophysics 11, no. 1 (March 1, 2006): 43–52. http://dx.doi.org/10.2113/jeeg11.1.43.

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Pasion, Leonard R., and Douglas W. Oldenburg. "A Discrimination Algorithm for UXO Using Time Domain Electromagnetics." Journal of Environmental and Engineering Geophysics 6, no. 2 (June 2001): 91–102. http://dx.doi.org/10.4133/jeeg6.2.91.

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Pippett, Timothy, and Stephen Lee. "UXO Location using Total Field Magnetics in SE Asia." ASEG Extended Abstracts 2004, no. 1 (December 2004): 1–2. http://dx.doi.org/10.1071/aseg2004ab114.

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Young, J. A., S. T. Keenan, D. A. Clark, K. E. Leslie, P. Sullivan, P. Fairman, C. Williams, C. P. Foley, and S. D. Billings. "A Superconducting Magnetic Tensor Gradiometer for Underwater UXO Detection." ASEG Extended Abstracts 2010, no. 1 (December 2010): 1–4. http://dx.doi.org/10.1081/22020586.2010.12041889.

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Bucaro, J. A., B. H. Houston, M. Saniga, L. R. Dragonette, T. Yoder, S. Dey, L. Kraus, and L. Carin. "Broadband acoustic scattering measurements of underwater unexploded ordnance (UXO)." Journal of the Acoustical Society of America 123, no. 2 (February 2008): 738–46. http://dx.doi.org/10.1121/1.2821794.

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Chirgwin, Carl. "Managing land mine and UXO contamination in exploration projects." Leading Edge 24, no. 4 (April 2005): 376–77. http://dx.doi.org/10.1190/1.1901387.

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Lin-Ping Song, Douglas W. Oldenburg, L. R. Pasion, S. D. Billings, and L. Beran. "Temporal Orthogonal Projection Inversion for EMI Sensing of UXO." IEEE Transactions on Geoscience and Remote Sensing 53, no. 2 (February 2015): 1061–72. http://dx.doi.org/10.1109/tgrs.2014.2332992.

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Forbes, Jonathan A., Ian Laughlin, Shane Newberry, Michael Ryhn, Jason Pasley, and Travis Newberry. "Stratification of risk to the surgical team in removal of small arms ammunition implanted in the craniofacial region: case report." Journal of Neurosurgery 125, no. 3 (September 2016): 661–66. http://dx.doi.org/10.3171/2015.6.jns15779.

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In cases of penetrating injury with implantation of small arms ammunition, it can often be difficult to tell the difference between simple ballistics and ballistics associated with unexploded ordnances (UXOs). In the operative environment, where highly flammable substances are often close to the surgical site, detonation of UXOs could have catastrophic consequences for both the patient and surgical team. There is a paucity of information in the literature regarding how to evaluate whether an implanted munition contains explosive material. This report describes a patient who presented during Operation Enduring Freedom with an implanted munition suspicious for a UXO and the subsequent workup organized by Explosive Ordnance Disposal (EOD) Company prior to surgical removal. Clinical risk factors for UXOs include assassination attempts and/or wartime settings. Specific radiological features suggestive of a UXO include projectile size greater than 7.62-mm caliber, alterations in density of the tip, as well as radiological evidence of a hollowed-out core. If an implanted UXO is suspected, risks to the surgical and anesthesia teams can be minimized by notifying the nearest military installation with EOD capabilities and following clinical practice guidelines set forth by the Joint Theater Trauma System.

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Tebbal, Ibtissam, and Abdelhak Ferhat Hamida. "Effects of Crossover Operators on Genetic Algorithms for the Extraction of Solar Cell Parameters from Noisy Data." Engineering, Technology & Applied Science Research 13, no. 3 (June 2, 2023): 10630–37. http://dx.doi.org/10.48084/etasr.5417.

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This study analyzed the accuracy of solar cell modeling parameters extracted from noisy data using Genetic Algorithms (GAs). Three crossover operators (XOs) were examined, namely the Uniform (UXO), Arithmetic (AXO), and Blend (BXO) operators. The data used were an experimental benchmark cell and a simulated curve where noise levels (p) from 0 to 10% were added. For each XO, the analysis was carried out by running GAs 100 times and varying p and population size (Npop). Simulation results showed that UXO and AXO suffered from premature convergence and failed to provide parameters with good precision even with very high Npop, although they provided good fitting. In all analyzed cases, BXO outperformed UXO and AXO and the results showed that it can compete with the most efficient methods. For the benchmark curve, BXO reproduced the best RMSE found in the literature (0.7730062 mA) while providing the exact values of the parameters and a very low RMSE (1E-13) for the clean curve (p=0). For noisy curves, the errors of the extracted parameters were smaller than 10% for p lower than or equal to 6%. For higher values of p, the errors were smaller than 30%.

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Journal articles on the topic 'UXO'

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