Dr. Benjamin E. Barrowes Profile

Dr. Benjamin E. Barrowes

Electrical Engineer at US Army Engineer Research and Development Ctr

SPIE Involvement:

Author

Publications (70)

Proceedings Article | 30 May 2022 Presentation + Paper

Wideband EMI signatures of conductive pipes and wires

Sven Isaacson, Benjamin Barrows, Fridon Shubitidze

Proceedings Volume 12116, 1211616 (2022) https://doi.org/10.1117/12.2619083

KEYWORDS: Magnetism, Signal detection, Transmitters, Electromagnetic coupling, Target detection, Electromagnetism, Corrosion, Magnetic sensors, Lead, Image segmentation

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Proceedings Article | 12 April 2021 Presentation + Paper

Electromagnetic induction sensing of unexploded ordinance and soil properties from unmanned aerial systems

Randall Reynolds, Benjamin Barrowes, Tornike Shubitidze, Caylin Hartshorn, Brian Quinn, Fridon Shubitidze

Proceedings Volume 11750, 1175002 (2021) https://doi.org/10.1117/12.2585537

KEYWORDS: Sensors, Electromagnetic coupling, Electromagnetism, Sensing systems, Target detection, Soil contamination, Unexploded object detection, Transmitters, Receivers, Magnetism

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Proceedings Article | 12 April 2021 Presentation + Paper

Buried IED targets detection and identification using advanced HFEMI models

Fridon Shubitidze, Benjamin Barrowes, Guy Jutras

Proceedings Volume 11750, 1175004 (2021) https://doi.org/10.1117/12.2588151

KEYWORDS: Improvised explosive devices, Data modeling, Target detection, Electromagnetic coupling, Improvised explosive device detection, Standards development, Signal processing, Sensors, Roads, Ground penetrating radar

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Proceedings Article | 12 April 2021 Presentation + Paper

Magnetic nanoparticles response to low frequency induction heating in rigid matrices

Michele Maxson, Benjamin Barrowes, Fridon Shubitidze

Proceedings Volume 11723, 117230D (2021) https://doi.org/10.1117/12.2587756

KEYWORDS: Matrices, Magnetism, Nanoparticles, Polyurethane, Particles, Iron, Carbon, Cancer, Biomedical optics, Biological research

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Proceedings Article | 12 April 2021 Presentation + Paper

High frequency EMI sensing for detection and location of underground metallic utilities

Sven Isaacson, Caylin Hartshorn, Benjamin Barrowes, Fridon Shubitidze

Proceedings Volume 11750, 1175003 (2021) https://doi.org/10.1117/12.2588033

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Proceedings Article | 10 May 2019 Presentation + Paper

Investigating time domain EMI signals diffusion in a conducting environment for UXO detection and classification

Fridon Shubitidze, Benjamin Barrowes, O'Neill

Proceedings Volume 11012, 110120X (2019) https://doi.org/10.1117/12.2519213

KEYWORDS: Electromagnetic coupling, Magnetism, Environmental sensing, Electromagnetism, Signal detection, Target detection, Diffusion, Sensors, Optical spheres, Unexploded object detection

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Proceedings Article | 10 May 2019 Presentation + Paper

Analysis of the effect of salt water on time domain electromagnetic induction sensing of submerged metallic objects

Kevin O'Neill, Fridon Shubitidze, Benjamin Barrowes

Proceedings Volume 11012, 110120I (2019) https://doi.org/10.1117/12.2519181

KEYWORDS: Sensors, Electromagnetism, Copper, Electromagnetic coupling, Magnetism, Diffusion, Solids, Computer simulations, Commercial off the shelf technology

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Proceedings Article | 10 May 2019 Presentation + Paper

HFEMI data from carbon rods, wires, and improvised explosive device constituent parts

Benjamin Barrowes, Danney Glaser, Mikheil Prishvin, Guy Jutras, Kevin O'Neill, Fridon Shubitidze

Proceedings Volume 11012, 110120Q (2019) https://doi.org/10.1117/12.2519048

KEYWORDS: Improvised explosive devices, Carbon, Electromagnetic coupling, Sensors, Electromagnetism, Metals, Land mines, Target detection, Magnetism, Data acquisition

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Proceedings Article | 8 May 2018 Presentation + Paper

Accounting for the influence of salt water in the physics required for processing underwater UXO EMI signals

Fridon Shubitidze, Benjamin Barrowes, Irma Shamatava , John Sigman, Kevin O'Neill

Proceedings Volume 10628, 106280L (2018) https://doi.org/10.1117/12.2305161

KEYWORDS: Physics, Signal processing, Electromagnetic coupling, Submerged target modeling, Environmental sensing, Electromagnetism, Instrument modeling, Sensors

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Proceedings Article | 30 April 2018 Presentation + Paper

High frequency EMI sensing for estimating depleted uranium radiation levels in soil

Fridon Shubitidze, Benjamin Barrowes, John Ballard, Ron Unz, Adam Randle, Steve Larson, Kevin O'Neill

Proceedings Volume 10628, 106280O (2018) https://doi.org/10.1117/12.2305259

KEYWORDS: Uranium, Soil contamination, Electromagnetic coupling, Metals, Sodium, Sensors, Contamination, Soil science, Data modeling, Magnetism

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This paper studies high (100 kHz up to 15 MHz) frequency electromagnetic responses (HFEMI) for DU metallic pieces and DU contaminated soils and derives a simple empirical expression from the measured HFEMI data for estimating DU contamination levels in soil. Depleted uranium (DU) is the byproduct of uranium enrichment and contains 33% less radioactive isotopes than natural uranium. There are at least thirty facilities at fourteen separate locations in the US, where munitions containing DU have been evaluated or used for training. At these sites, which vary in size, evaluation studies have been conducted with and without catch boxes. In addition, the DoD used DU at open firing ranges as large as thousands of acres (hundreds of hectares), for both artillery and aircraft training. These activities have left a legacy of DU contamination. Currently at military sites where DU munitions have been or are being used, cleanup activities mainly are done by excavating and shipping large volumes of site soil and berm materials to a hazardous material radiation disposal site. This approach is very time consuming, costly, and associated with the potential for exposure of personnel performing excavation and transportation. It also limits range use during the operation. So, there is an urgent need for technologies for rapid surveying of large areas to detect, locate, and removal of DU contaminants at test sites. Additionally, the technologies are needed to detect material at a depth of at least 30 cm as well as discriminate between DU metals and oxides from natural uranium and from other conductive metals such as natural and man-made range clutter. One of the potential technologies for estimating DU radiation levels in soils is HFEMI sensing. In this paper, HFEMI signals are collected for DU metal pieces, sodium diunarate (Na₂U₂ O₃) and tri-uranium octoxide (U₃O₈). The EMI signal’s sensitivity with respect to DU material composition and conditions are illustrated and analyzed. A new scheme for extracting near-surface soil’s EM parameters is formulated.

Proceedings Article | 30 April 2018 Presentation + Paper

Short and long wire detection using high-frequency electromagnetic induction techniques

Benjamin Barrowes, Danney Glaser, Mikheil Prishvin, Kevin O'Neill, Fridon Shubitidze

Proceedings Volume 10628, 106280K (2018) https://doi.org/10.1117/12.2304059

KEYWORDS: Electromagnetism, Magnetism, Electromagnetic coupling, Sensors, Improvised explosive devices, Target detection, Metals, Receivers, Antennas

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Proceedings Article | 30 April 2018 Presentation + Paper

EMI real-time subsurface target location by analytical dHP

Kevin O'Neill, Fridon Shubitidze, Benjamin Barrowes

Proceedings Volume 10628, 106280N (2018) https://doi.org/10.1117/12.2305177

KEYWORDS: Sensors, Condition numbers, Electromagnetic coupling, Magnetism, Receivers, Calibration, Electromagnetism, Computer simulations, Submerged target modeling, Signal processing

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Proceedings Article | 4 May 2017 Presentation + Paper

A hybrid coil system for high frequency electromagnetic induction sensing

John Sigman, Benjamin Barrowes, Yinlin Wang, Hollis Bennett, Janet Simms, Donald Yule, Kevin O'Neill, Fridon Shubitidze

Proceedings Volume 10182, 101820F (2017) https://doi.org/10.1117/12.2263198

KEYWORDS: Electromagnetic coupling, Signal to noise ratio, Electromagnetism, Target detection, Sensors, Optical spheres, Composites, Land mines

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Proceedings Article | 4 May 2017 Paper

Ultra-wide-band EMI sensing for subsurface deplete uranium detection and classification

Fridon Shubitidze, Benjamin Barrowes, John Sigman, Yinlin Wang, Janet Simms, Hollis Bennett, Don Yule, Steven Larson, Kevin O'Neill

Proceedings Volume 10182, 1018216 (2017) https://doi.org/10.1117/12.2262950

KEYWORDS: Uranium, Electromagnetic coupling, Sensors, Defense and security, Aerosols, Combustion, Metals, Contamination, Environmental management, Soil contamination, Data modeling, Magnetism, Soil science, Receivers, Electromagnetism

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Proceedings Article | 3 May 2017 Presentation + Paper

Void and landmine detection using the HFEMI sensor

Benjamin Barrowes, Fridon Shubitidze, John Sigman, Jay Bennett, Janet Simms, Don Yule, Kevin O'Neill

Proceedings Volume 10182, 1018210 (2017) https://doi.org/10.1117/12.2262619

KEYWORDS: Data modeling, Data acquisition, Optical spheres, Electromagnetism, Land mines, Carbon, Sensors, Target detection, Electromagnetic coupling

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Proceedings Article | 19 May 2016 Paper

A high power EMI sensor for detecting and classifying small and deep targets

F. Shubitidze, B. Barrowes, Yinlin Wang, Irma Shamatava, J. Sigman, K. O'Neil, Daniel Steinhurst

Proceedings Volume 9823, 982308 (2016) https://doi.org/10.1117/12.2224407

KEYWORDS: Systems modeling, Sensors, Electromagnetic coupling, Target detection, Transmitters, Electromagnetism, Receivers, Magnetism, Data modeling, Data processing

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Proceedings Article | 17 May 2016 Paper

Advanced EMI models for survey data processing: targets detection and classification

F. Shubitidze, B. Barrowes, Yinlin Wang, Irma Shamatava, J. Sigman, K. O'Neill

Proceedings Volume 9823, 98230O (2016) https://doi.org/10.1117/12.2224420

KEYWORDS: Data modeling, Electromagnetic coupling, Target detection, Magnetism, Electromagnetism, Sensors, Data processing, Polarizability, Detection and tracking algorithms, Associative arrays

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Proceedings Article | 17 May 2016 Paper

Coil design considerations for a high-frequency electromagnetic induction sensing instrument

John Sigman, Benjamin Barrowes, Yinlin Wang, Hollis Bennett, Janet Simms, Donald Yule, Kevin O'Neill, Fridon Shubitidze

Proceedings Volume 9823, 982302 (2016) https://doi.org/10.1117/12.2223988

KEYWORDS: Electromagnetism, Carbon, Signal to noise ratio, Transmitters, Electromagnetic coupling, Data modeling, Sensors, Inductive coupling, Improvised explosive devices, Prototyping

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Proceedings Article | 3 May 2016 Paper

Carbon fiber and void detection using high-frequency electromagnetic induction techniques

Benjamin Barrowes, John Sigman, YinLin Wang, Kevin O'Neill, Fridon Shubitidze, Janet Simms, Hollis Bennett, Donald Yule

Proceedings Volume 9823, 98230D (2016) https://doi.org/10.1117/12.2224584

KEYWORDS: Electromagnetism, Carbon, Electromagnetic coupling, Metals, Magnetism, Sensors, Optical spheres, Diffusion, Dielectrics, Physics

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Proceedings Article | 9 June 2014 Paper

Automatic classification of unexploded ordnance applied to live sites for MetalMapper sensor

John Brevard Sigman, Kevin O'Neill, Benjamin Barrowes, Yinlin Wang, Fridon Shubitidze

Proceedings Volume 9072, 90720F (2014) https://doi.org/10.1117/12.2050784

KEYWORDS: Sensors, Polarizability, Data modeling, Detection and tracking algorithms, Magnetic sensors, Magnetism, Machine learning, Electromagnetism, Electromagnetic coupling, Transmitters

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Proceedings Article | 9 June 2014 Paper

A combined joint diagonalization-MUSIC algorithm for subsurface targets localization

Yinlin Wang, John Sigman, Benjamin Barrowes, Kevin O'Neill, Fridon Shubitidze

Proceedings Volume 9072, 90720G (2014) https://doi.org/10.1117/12.2050787

KEYWORDS: Interference (communication), Detection and tracking algorithms, Signal to noise ratio, Sensors, Matrices, Electromagnetic coupling, Electromagnetism, Electronic filtering, Detector arrays, Algorithm development

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Proceedings Article | 9 June 2014 Paper

Detecting and classifying small and deep targets using improved EMI hardware and data processing approach

F. Shubitidze, B. Barrowes, J. Sigman, Yinlin Wang, Irma Shamatava, K. O'Neill

Proceedings Volume 9072, 90720I (2014) https://doi.org/10.1117/12.2050893

KEYWORDS: Electromagnetic coupling, Target detection, Data modeling, Sensors, Transmitters, Signal to noise ratio, Magnetism, Data processing, Polarizability, Interference (communication)

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Proceedings Article | 9 June 2014 Paper

Advanced EMI models for survey data processing: targets detection and classification

F. Shubitidze, J. Sigman, Yinlin Wang, J. Miller, J. Keranen, I. Shamatava, B. Barrowes, K. O'Neill

Proceedings Volume 9072, 90720J (2014) https://doi.org/10.1117/12.2050897

KEYWORDS: Electromagnetic coupling, Data modeling, Target detection, Magnetism, Data processing, Transmitters, Sensors, Detection and tracking algorithms, Systems modeling, Polarizability

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One of the most challenging aspects of survey data processing is target selection. The fundamental input for the classification is dynamic data collected along survey lines. These data are different from the static data obtained in cued mode and used for target classification. Survey data are typically collected using just one transmitter loop (the Z-axis loop) and feature short data point collection times and short decay transience. The collection intervals for each data point are typically 0.1 s, and the signal repetition rates are typically 90 or 270 Hz (in other words, the transient decay times are 2.7 ms or 0.9 ms). Reliable classification requires multiple side/angle illumination; i.e., to conduct reliable classification it is necessary to combine and jointly invert multiple data points. However, picking data points that provide optimal information for classifying targets is a difficult task. The traditional method plots signal amplitudes on a 2D map and picks peaks of signal level without properly accounting for the underlying physics. In this paper, the joint diagonalization is applied to survey data sets to improve data pre-processing and target picking. The JD technique is an EMI data analysis and target classification technique and is applicable for all next-generation multi-static array EMI sensors. The method extracts multi-static response data matrix eigenvalues. The eigenvalues are main characteristics of the data. Recent studies have demonstrated that the method has great potential to quickly estimate the number of potential targets and moreover classify these targets at the data pre-processing stage, in real time and without the need for a forward model. Another advantage of JD is that it provides the ability to separate signal from noise making it possible to de-noise data without distorting the signal due to the targets. In this paper the JD technique is used to process dynamic data collected at South West Proving Ground and Aberdeen Proving Ground (APG) sites using the 2 × 2 TEMTADS and OPTEMA systems, respectively. The joint eigenvalues are extracted as functions of time for each data point and summed/stacked together before being used to create detection maps. Once targets are detected, a set of data is chosen for each anomaly and inverted using the ortho-normalized volume magnetic source technique.

Proceedings Article | 29 May 2014 Paper

Homemade explosives in the subsurface as intermediate electrical conductivity materials: a new physical principle for their detection

Steven Grant, Benjamin Barrowes, Fridon Shubitidze, Steven Arcone

Proceedings Volume 9072, 90720A (2014) https://doi.org/10.1117/12.2050430

KEYWORDS: Electromagnetic coupling, Electromagnetism, Data modeling, Explosives, Magnetism, Instrument modeling, Improvised explosive devices, Humidity, Metals, Target detection

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Proceedings Article | 7 June 2013 Paper

The Pedemis Instrument: operation and APG field results

Benjamin Barrowes, Tomasz Grzegorczyk, Fridon Shibitidze, Pablo Fernández, Kevin O'Neill

Proceedings Volume 8709, 870903 (2013) https://doi.org/10.1117/12.2014964

KEYWORDS: Sensors, Receivers, Data acquisition, Electromagnetic coupling, Transmitters, Data modeling, Electromagnetism, Signal detection, Magnetism, Target detection

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Proceedings Article | 7 June 2013 Paper

A new EMI system for detection and classification of challenging targets

F. Shubitidze, J. Fernández, B. Barrowes, K. O'Neill

Proceedings Volume 8709, 870906 (2013) https://doi.org/10.1117/12.2016349

KEYWORDS: Sensors, Electromagnetic coupling, Target detection, Transmitters, Data modeling, Magnetism, Classification systems, Electromagnetism, Target acquisition, Receivers

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Proceedings Article | 7 June 2013 Paper

Target-classification approach applied to active UXO sites

F. Shubitidze, J. Fernández, Irma Shamatava, B. Barrowes, K. O'Neill

Proceedings Volume 8709, 870907 (2013) https://doi.org/10.1117/12.2016351

KEYWORDS: Magnetism, Electromagnetic coupling, Data modeling, Library classification systems, Sensors, Detection and tracking algorithms, Rockets, Performance modeling, Defense and security, Mathematical modeling

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Proceedings Article | 7 June 2013 Paper

Spencer Range live-site portable EMI sensors target classification

I. Shamatava, J. Fernández, B. Barrowes, K. O'Neill, F. Shubitidze

Proceedings Volume 8709, 870905 (2013) https://doi.org/10.1117/12.2016354

KEYWORDS: Data modeling, Electromagnetic coupling, Magnetism, Sensors, Library classification systems, Detection and tracking algorithms, Receivers, Transmitters, Mathematical modeling, Optimization (mathematics)

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Proceedings Article | 7 June 2013 Paper

Automatic classification of unexploded ordnance applied to Spencer Range live site for 5x5 TEMTADS sensor

John Sigman, Benjamin Barrowes, Kevin O'Neill, Fridon Shubitidze

Proceedings Volume 8709, 870904 (2013) https://doi.org/10.1117/12.2016118

KEYWORDS: Sensors, Magnetism, Detection and tracking algorithms, Data modeling, Electromagnetism, Electromagnetic coupling, Receivers, Transmitters, Polarizability, Weapons

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Proceedings Article | 7 June 2013 Paper

Toward a real-time positioning system for a portable EMI sensor

Juan Pablo Fernández, Benjamin Barrowes, Kevin O'Neill, Irma Shamatava, Fridon Shubitidze

Proceedings Volume 8709, 870902 (2013) https://doi.org/10.1117/12.2016245

KEYWORDS: Receivers, Transmitters, Sensors, Electromagnetic coupling, Electromagnetism, Telecommunications, Algorithm development, Target detection, Data acquisition, Inductance

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Proceedings Article | 1 June 2012 Paper

Camp Beale live-site handheld-sensor data inversion and classification using advanced EMI models

I. Shamatava, J. Fernández, B. Barrowes, K. O'Neill, A. Bijamov, F. Shubitidze

Proceedings Volume 8357, 835706 (2012) https://doi.org/10.1117/12.919586

KEYWORDS: Data modeling, Electromagnetic coupling, Sensors, Detection and tracking algorithms, Magnetism, 3D acquisition, Library classification systems, Transmitters, Analytical research, 3D modeling

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Proceedings Article | 18 May 2012 Paper

Inversion-free discrimination of unexploded ordnance in real time

F. Shubitidze, J. Fernández, I. Shamatava, A. Luperon, B. Barrowes, K. O'Neill, A. Bijamov

Proceedings Volume 8357, 835705 (2012) https://doi.org/10.1117/12.919549

KEYWORDS: Sensors, Electromagnetic coupling, Matrices, Transmitters, Detection and tracking algorithms, Metals, Receivers, Data modeling, Electromagnetism, Magnetism

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Proceedings Article | 11 May 2012 Paper

Inversion and classification studies of live-site production-level MetalMapper data sets

F. Shubitidze, J. Fernández, J. Miller, J. Keranen, B. Barrowes, A. Bijamov

Proceedings Volume 8357, 835704 (2012) https://doi.org/10.1117/12.919565

KEYWORDS: Data modeling, Electromagnetic coupling, Magnetism, Sensors, Data processing, Library classification systems, Analytical research, Performance modeling, Mathematical modeling, Transmitters

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Proceedings Article | 11 May 2012 Paper

Optimizing EMI transmitter and receiver configurations to enhance detection and identification of small and deep metallic targets

Juan Pablo Fernández, Benjamin Barrowes, Alex Bijamov, Kevin O'Neill, Irma Shamatava, Daniel Steinhurst, Fridon Shubitidze

Proceedings Volume 8357, 835703 (2012) https://doi.org/10.1117/12.919588

KEYWORDS: Transmitters, Target detection, Signal to noise ratio, Sensors, Receivers, Electromagnetic coupling, Matrices, Magnetism, General packet radio service, Scanning laser ophthalmoscopy

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Proceedings Article | 11 May 2012 Paper

Pedemis: a portable electromagnetic induction sensor with integrated positioning

Benjamin Barrowes, Fridon Shubitidze, Tomasz Grzegorczyk, Pablo Fernández, Kevin O'Neill

Proceedings Volume 8357, 835702 (2012) https://doi.org/10.1117/12.918321

KEYWORDS: Data acquisition, Receivers, Sensors, Transmitters, Electromagnetic coupling, Electromagnetism, Data modeling, Target detection, Magnetism, Optical spheres

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Proceedings Article | 31 May 2011 Paper

EMI sensor positioning using a beacon approach

Nicolas Lhomme, Benjamin Barrowes, David George

Proceedings Volume 8017, 80170C (2011) https://doi.org/10.1117/12.886642

KEYWORDS: Sensors, Receivers, Transmitters, Electromagnetic coupling, Global Positioning System, Magnetism, Polarizability, Classification systems, Head, Electromagnetism

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Proceedings Article | 31 May 2011 Paper

Advanced UXO discrimination: resolving multiple targets and overlapping EMI signals

Fridon Shubitidze, Benjamin Barrowes, Irma Shamatava, Juan Pablo Fernandez, Alex Bijamov, Kevin O'Neill

Proceedings Volume 8017, 80170A (2011) https://doi.org/10.1117/12.884405

KEYWORDS: Electromagnetic coupling, Data modeling, Sensors, Magnetism, Mathematical modeling, Transmitters, Receivers, Matrices, Target detection, Detection and tracking algorithms

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Proceedings Article | 23 May 2011 Paper

Rapid position estimation using electromagnetic induction data from the MetalMapper in dynamic mode

Tomasz Grzegorczyk, Benjamin Barrowes, David George, Fridon Shubitidze, J. Fernández, Kevin O'Neill

Proceedings Volume 8017, 801705 (2011) https://doi.org/10.1117/12.884059

KEYWORDS: Sensors, Polarizability, Receivers, Optical spheres, Magnetism, Detection and tracking algorithms, Electromagnetism, Calibration, Electromagnetic coupling, Scanning laser ophthalmoscopy

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Proceedings Article | 23 May 2011 Paper

Comparison of supervised and unsupervised machine learning techniques for UXO classification using EMI data

Alex Bijamov, Fridon Shubitidze, Juan Pablo Fernandez, Irma Shamatava, Benjamin Barrowes, Kevin O'Neill

Proceedings Volume 8017, 801706 (2011) https://doi.org/10.1117/12.884076

KEYWORDS: Electromagnetic coupling, Neural networks, Neurons, Magnetism, Machine learning, Data modeling, Receivers, Feature extraction, Scanning laser ophthalmoscopy, Transmitters

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Proceedings Article | 23 May 2011 Paper

MPV-II: an enhanced vector man-portable EMI sensor for UXO identification

Juan Pablo Fernández, Benjamin Barrowes, Alex Bijamov, Tomasz Grzegorczyk, Nicolas Lhomme, Kevin O'Neill, Irma Shamatava, Fridon Shubitidze

Proceedings Volume 8017, 801707 (2011) https://doi.org/10.1117/12.884085

KEYWORDS: Sensors, Receivers, Polarizability, Data modeling, Transmitters, Electromagnetic coupling, Head, Electromagnetism, Magnetism, Telecommunications

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Proceedings Article | 23 May 2011 Paper

Live-site UXO classification studies using advanced EMI and statistical models

I. Shamatava, F. Shubitidze, J. Fernandez, A. Bijamov, B. Barrowes, K. O'Neill

Proceedings Volume 8017, 801709 (2011) https://doi.org/10.1117/12.884404

KEYWORDS: Electromagnetic coupling, Data modeling, Detection and tracking algorithms, Sensors, Statistical analysis, Magnetism, Transmitters, Library classification systems, Copper, Feature extraction

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Proceedings Article | 29 April 2010 Paper

SLO blind data set inversion and classification using physically complete models

I. Shamatava, F. Shubitidze, J. Fernández, B. Barrowes, K. O'Neill, T. Grzegorczyk, A. Bijamov

Proceedings Volume 7664, 766404 (2010) https://doi.org/10.1117/12.850621

KEYWORDS: Metals, Sensors, Data modeling, Scanning laser ophthalmoscopy, Electromagnetic coupling, Magnetism, Rockets, Calibration, Detection and tracking algorithms, Transmitters

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Proceedings Article | 29 April 2010 Paper

Combining electromagnetic induction and automated classification in a UXO discrimination blind test

Juan Pablo Fernández, Benjamin Barrowes, Alex Bijamov, Tomasz Grzegorczyk, Kevin O'Neill, Irma Shamatava, Fridon Shubitidze

Proceedings Volume 7664, 766403 (2010) https://doi.org/10.1117/12.850446

KEYWORDS: Electromagnetism, Sensors, Magnetism, Calibration, Electromagnetic coupling, Detection and tracking algorithms, Data modeling, Binary data, Polarizability, Optimization (mathematics)

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Proceedings Article | 29 April 2010 Paper

Comparison of the physically complete model with a simple dipole model for UXO detection and discrimination

F. Shubitidze, J. P. Fernández, B. Barrowes, Kevin O'Neill, I. Shamatava, A. Bijamov

Proceedings Volume 7664, 766408 (2010) https://doi.org/10.1117/12.850654

KEYWORDS: Data modeling, Magnetism, Electromagnetic coupling, Polarizability, Detection and tracking algorithms, Sensors, Scanning laser ophthalmoscopy, Calibration, Receivers, Electromagnetism

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Proceedings Article | 29 April 2010 Paper

Upward continuation of EMI data for sensing of subsurface UXO in cluttered, multi-object cases

Kevin O'Neill, Benjamin Barrowes, Fridon Shubitidze, Juan Pablo Fernandez, Tomasz Grzegorczyk, Irma Shamatava

Proceedings Volume 7664, 76640C (2010) https://doi.org/10.1117/12.850441

KEYWORDS: Sensors, Electromagnetic coupling, Magnetism, Receivers, Data modeling, Nose, Electromagnetism, Polarizability, Magnetometers, Free space

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Proceedings Article | 29 April 2010 Paper

Assessing EMI noise due to the marine environment to enhance underwater UXO detection and discrimination

Alex Bijamov, Fridon Shubitidze, Juan Pablo Fernandez, Irma Shamatava, Benjamin Barrowes, Kevin O'Neill

Proceedings Volume 7664, 76640W (2010) https://doi.org/10.1117/12.850628

KEYWORDS: Magnetism, Water, Unexploded object detection, Sensors, Electromagnetic coupling, Surface roughness, Oceanography, Environmental sensing, Interfaces, Electromagnetism

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Proceedings Article | 29 April 2010 Paper

Applying a volume dipole distribution model to next-generation sensor data for multi-object data inversion and discrimination

Fridon Shubitidze, David Karkashadze, Juan Pablo Fernández, Benjamin Barrowes, Kevin O'Neill, Tomasz Grzegorczyk, Irma Shamatava

Proceedings Volume 7664, 766407 (2010) https://doi.org/10.1117/12.850651

KEYWORDS: Magnetism, Sensors, Data modeling, Electromagnetic coupling, Detection and tracking algorithms, Transmitters, Receivers, Target detection, Magnetic sensors, Signal detection

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Proceedings Article | 28 April 2010 Paper

Kalman filters applied to the detection of unexploded ordnance

Tomasz Grzegorczyk, Benjamin Barrowes, Fridon Shubitidze, J. Fernández, Irma Shamatava, Kevin O'Neill

Proceedings Volume 7664, 766402 (2010) https://doi.org/10.1117/12.848564

KEYWORDS: Filtering (signal processing), Polarizability, Magnetism, Sensors, Detection and tracking algorithms, Electromagnetic coupling, Metals, Electromagnetism, Interference (communication), Transmitters

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