Dr. Jay A. Marble Profile

Dr. Jay A. Marble

Student at US Army CCDC C5ISR Ctr Night Vision & Electronic Sensors Directorate

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Publications (21)

Proceedings Article | 29 April 2010 Paper

Adapting physically complete models to vehicle-based EMI array sensor data: data inversion and discrimination studies

Fridon Shubitidze, Jonathan Miller, Gregory Schultz, Jay Marble

Proceedings Volume 7664, 76640A (2010) https://doi.org/10.1117/12.850636

KEYWORDS: Data modeling, Magnetism, Electromagnetic coupling, Sensors, Mathematical modeling, Magnetic sensors, Receivers, Transmitters, Target detection, Polarizability

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This paper reports vehicle based electromagnetic induction (EMI) array sensor data inversion and discrimination results. Recent field studies show that EMI arrays, such as the Minelab Single Transmitter Multiple Receiver (STMR), and the Geophex GEM-5 EMI array, provide a fast and safe way to detect subsurface metallic targets such as landmines, unexploded ordnance (UXO) and buried explosives. The array sensors are flexible and easily adaptable for a variety of ground vehicles and mobile platforms, which makes them very attractive for safe and cost effective detection operations in many applications, including but not limited to explosive ordnance disposal and humanitarian UXO and demining missions. Most state-of-the-art EMI arrays measure the vertical or full vector field, or gradient tensor fields and utilize them for real-time threat detection based on threshold analysis. Real field practice shows that the threshold-level detection has high false alarms. One way to reduce these false alarms is to use EMI numerical techniques that are capable of inverting EMI array data in real time. In this work a physically complete model, known as the normalized volume/surface magnetic sources (NV/SMS) model is adapted to the vehicle-based EMI array, such as STMR and GEM-5, data. The NV/SMS model can be considered as a generalized volume or surface dipole model, which in a special limited case coincides with an infinitesimal dipole model approach. According to the NV/SMS model, an object's response to a sensor's primary field is modeled mathematically by a set of equivalent magnetic dipoles, distributed inside the object (i.e. NVMS) or over a surface surrounding the object (i.e. NSMS). The scattered magnetic field of the NSMS is identical to that produced by a set of interacting magnetic dipoles. The amplitudes of the magnetic dipoles are normalized to the primary magnetic field, relating induced magnetic dipole polarizability and the primary magnetic field. The magnitudes of the NSMS are determined directly by minimizing the difference between measured and modeled data for any known object and any type of EMI sensor data. The EMI array data are inverted via the combined NV/SMS and differential evolution inversion method that uses a search scheme to estimate the location of the target. First, the applicability of the NV/SMS and DE algorithms to STMR and GEM-5 data sets is demonstrated by comparing the modeled data against the actual data, and finally the discrimination studies are conducted using as discrimination parameters the total NV/SMS and the principal axis of the induced magnetic polarizability tensor for each target.

Proceedings Article | 29 April 2010 Paper

Dual-EMI system for object classification

Jay Marble, Ian McMichael

Proceedings Volume 7664, 76640B (2010) https://doi.org/10.1117/12.850084

KEYWORDS: Sensors, Metals, Target detection, Detection and tracking algorithms, Roads, Classification systems, Calibration, Transmitters, Algorithm development, Receivers

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Proceedings Article | 29 April 2010 Paper

Outdoor synthetic aperture acoustic ground target measurements

Steven Bishop, Therese-Ann Ngaya, Joe Vignola, John Judge, Jay Marble, Peter Gugino, Mehrdad Soumekh, Erik Rosen

Proceedings Volume 7664, 76641Y (2010) https://doi.org/10.1117/12.851802

KEYWORDS: Acoustics, Transceivers, Optical spheres, Synthetic aperture radar, Foam, Metals, Reconstruction algorithms, Spherical lenses, Image processing, Wavefront reconstruction

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Proceedings Article | 29 April 2010 Paper

Target localization techniques for vehicle-based electromagnetic induction array applications

Jonathan Miller, Gregory Schultz, Fridon Shubitidze, Jay Marble

Proceedings Volume 7664, 766406 (2010) https://doi.org/10.1117/12.850411

KEYWORDS: Receivers, Magnetism, Sensors, Data modeling, Transmitters, Electromagnetic coupling, Inductance, Resistance, Optical spheres, Electromagnetism

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Proceedings Article | 29 April 2010 Paper

Dual sensor platforms for UXO/landmine detection using GPR and EMI

Jay Marble, Kevin Hong

Proceedings Volume 7664, 76641W (2010) https://doi.org/10.1117/12.853681

KEYWORDS: Sensors, Metals, Land mines, General packet radio service, Target detection, Ground penetrating radar, Detection and tracking algorithms, Electromagnetic coupling, Sensor performance, Unexploded object detection

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Proceedings Article | 5 May 2009 Paper

Metal detector depth estimation algorithms

Jay Marble, Ian McMichael

Proceedings Volume 7303, 73030L (2009) https://doi.org/10.1117/12.817868

KEYWORDS: Sensors, Detection and tracking algorithms, Metals, Receivers, Roads, Evolutionary algorithms, Transmitters, Target detection, General packet radio service, Inspection

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Proceedings Article | 29 April 2009 Paper

Proposed design of search radar for thin wire detection

Jay Marble, Steve Bishop

Proceedings Volume 7308, 73080H (2009) https://doi.org/10.1117/12.817866

KEYWORDS: Radar, Scattering, Chemical elements, Electromagnetic scattering, Image processing, Electromagnetism, Data processing, Polarization, Electromagnetic radiation, Metals

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Proceedings Article | 29 April 2008 Paper

Estimating object depth using a vertical gradient metal detector

Jay Marble, Ian McMichael, Denis Reidy

Proceedings Volume 6953, 695313 (2008) https://doi.org/10.1117/12.779575

KEYWORDS: Sensors, Metals, Roads, Magnetic sensors, Feature extraction, Time metrology, Error analysis, Radar, Magnetometers, Land mines

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Proceedings Article | 18 May 2006 Paper

Confirmation sensor scheduling using a reinforcement learning approach

Jay Marble, Doron Blatt, Alfred Hero

Proceedings Volume 6217, 62172V (2006) https://doi.org/10.1117/12.665900

KEYWORDS: Sensors, Land mines, Electromagnetic coupling, General packet radio service, Metals, Radar, Sensor technology, Image sensors, Nonmetals, Seismic sensors

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Proceedings Article | 8 May 2006 Paper

See Through The Wall detection and classification of scattering primitives

Jay Marble, Alfred Hero

Proceedings Volume 6210, 62100B (2006) https://doi.org/10.1117/12.665934

KEYWORDS: Radar, Scattering, Polarimetry, Data modeling, Unattended ground sensors, Sensors, Antennas, Radar imaging, Detection and tracking algorithms, Wave propagation

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Proceedings Article | 10 June 2005 Paper

Physics derived basis pursuit in buried object identification using EMI sensors

Jay Marble, Andrew Yagle, Gregory Wakefield

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.627949

KEYWORDS: Sensors, Metals, Polarizability, Optical spheres, Signal detection, Magnetism, Physics, Signal to noise ratio, Magnetic sensors, Electromagnetic coupling

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Proceedings Article | 10 June 2005 Paper

Sensor management for landmine detection

Jay Marble, Alfred Hero, Andrew Yagle

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.602756

KEYWORDS: Sensors, Land mines, Metals, Active remote sensing, Iron, Mining, General packet radio service, Electromagnetic coupling, Ground penetrating radar, Electromagnetism

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Proceedings Article | 10 June 2005 Paper

Multimodal adaptive landmine detection using EMI and GPR

Jay Marble, Andrew Yagle, Alfred Hero

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.602761

KEYWORDS: Sensors, Land mines, Electromagnetic coupling, General packet radio service, Metals, Environmental sensing, Mining, Electromagnetism, Dielectrics, Ground penetrating radar

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Proceedings Article | 21 September 2004 Paper

Measuring landmine size and burial depth with ground-penetrating radar

Jay Marble, Andrew Yagle

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.542222

KEYWORDS: Land mines, Radar, Metals, Ground penetrating radar, Sensors, Mining, General packet radio service, Image processing, Detection and tracking algorithms, Antennas

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Proceedings Article | 21 September 2004 Paper

The hyperbola-flattening transform

Jay Marble, Andrew Yagle

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.543793

KEYWORDS: Land mines, Radon transform, General packet radio service, Ground penetrating radar, Signal to noise ratio, Mining, Computer simulations, Mathematical modeling, Sensors, Signal processing

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Proceedings Article | 18 October 2001 Paper

Multisensor neural network approach to mine detection

Amber Iler, Jay Marble, Patrick Rauss

Proceedings Volume 4394, (2001) https://doi.org/10.1117/12.445429

KEYWORDS: Sensors, Neural networks, General packet radio service, Land mines, Metals, Target detection, Mining, Antennas, Infrared sensors, Forward looking infrared

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Proceedings Article | 18 October 2001 Paper

Landmine signatures in ground-penetrating radar

Jay Marble, Daren Wilcox, Russell Mersereau

Proceedings Volume 4394, (2001) https://doi.org/10.1117/12.445525

KEYWORDS: Land mines, Metals, Detection and tracking algorithms, General packet radio service, Radon transform, Ground penetrating radar, Dielectrics, Antennas, Sensors, 3D acquisition

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Proceedings Article | 22 August 2000 Paper

Sensor data fusion for mine detection from a vehicle-mounted system

Indar Bhatia, Vince Diehl, Tim Moore, Jay Marble, Ky Tran, Steven Bishop

Proceedings Volume 4038, (2000) https://doi.org/10.1117/12.396310

KEYWORDS: Sensors, Neural networks, Land mines, General packet radio service, Metals, Mining, Infrared sensors, Data fusion, Infrared signatures, Antennas

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Proceedings Article | 22 August 2000 Paper

Sensor fusion performance gain for buried mine/UXO detection using GPR, EMI, and MAG sensors

Jay Marble, John Ackenhusen, John Wegrzyn, Joseph Mancuso, Chris Dwan

Proceedings Volume 4038, (2000) https://doi.org/10.1117/12.396235

KEYWORDS: Sensors, General packet radio service, Land mines, Magnetometers, Electromagnetic coupling, Binary data, Iron, Metals, Magnetic sensors, Target detection

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Proceedings Article | 13 August 1999 Paper

Performance comparison of phenomenology-based features to generic features for false alarm reduction in UWB SAR imagery

Jay Marble, John Gorman

Proceedings Volume 3721, (1999) https://doi.org/10.1117/12.357640

KEYWORDS: Synthetic aperture radar, Image segmentation, Scattering, Optical filtering, Feature extraction, Target detection, Detection and tracking algorithms, Receivers, Analytical research, Radar

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Proceedings Article | 15 September 1998 Paper

Low-complexity multidiscriminant FOPEN target screener

John Gorman, Jay Marble

Proceedings Volume 3370, (1998) https://doi.org/10.1117/12.321835

KEYWORDS: Scattering, Target detection, Detection and tracking algorithms, Synthetic aperture radar, Polarimetry, Image filtering, Sensors, Signal attenuation, Device simulation, Radar

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Showing 5 of 21 publications

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