Newton, MA, United States
Newton, MA, United States

Time filter

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Fernandez J.P.,Unit 301 | Barrowes B.E.,U.S. Army | Grzegorczyk T.M.,Delpsi LLC | Lhomme N.,Sky Research, Inc. | And 3 more authors.
IEEE Sensors Journal | Year: 2011

The identification and discrimination of unexploded ordnance using low-frequency electromagnetic induction is an expensive and difficult process, typically beset by low data diversity and high positioning uncertainty. In this paper, we present the Man-Portable Vector (MPV) sensor, a new time-domain instrument designed to remedy these shortcomings by measuring all three vector components of the secondary magnetic field at five distinct points around each transmitter location. The MPV also has a laser positioning system that can give its location with millimeter precision. After describing the instrument in detail, we study its performance in various sets of measurements, using the tensor dipole model to analyze the data. We find that the sensor can detect deeply buried targets and identify some standard ordnance items. It can also resolve separate targets in cases where two objects share the field of view and produce overlapping signals. A new incarnation of the MPV, the MPV-II, is in an advanced stage of development. © 2006 IEEE.

Grzegorczyk T.M.,Delpsi LLC | Barrowes B.,United States ERDC Cold Regions Research and Engineering Laboratory | Shubitidze F.,Dartmouth College | Shubitidze F.,Sky Research, Inc. | And 3 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2010

The detection of unexploded ordnance (UXO) in the electromagnetic induction regime often suffers from a low signal to noise ratio due to the strong decay of the magnetic field. As a result, a deep UXO may be overshadowed by smaller yet shallower metal items which render the classification of the main target challenging. It is therefore desirable to have the ability to model the various sources of noise and to include them in a detection algorithm. Toward this effect, we investigate here Kalman and extended Kalman filters for the inversion of UXO polarizabilities and positions, respectively, within a dipole model approximation. Inherent to the method, our analysis is based on the assumption of Gaussian noise distribution, which is often reasonable. Results are shown on both synthetic and TEMTADS data which have been purposely corrupted with noise. In particular, the situation of a main target in the presence of dense clutter is investigated, whereby the clutter is composed of 16 nosepieces buried close to the sensor. © 2010 Copyright SPIE - The International Society for Optical Engineering.

Barrowes B.E.,USACE ERDC CRREL | Barrowes B.E.,Hanover College | Shubitidze F.,Hanover College | Grzegorczyk T.M.,Delpsi LLC | And 3 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2012

Pedemis (PortablE Decoupled Electromagnetic Induction Sensor) is a time-domain handheld electromagnetic induction (EMI) instrument with the intended purpose of improving the detection and classification of UneXploded Ordnance (UXO). Pedemis sports nine coplanar transmitters (the Tx assembly) and nine triaxial receivers held in a fixed geometry with respect to each other (the Rx assembly) but with that Rx assembly physically decoupled from the Tx assembly allowing flexible data acquisition modes and deployment options. The data acquisition (DAQ) electronics consists of the National Instruments (NI) cRIO platform which is much lighter and more energy efficient that prior DAQ platforms. Pedemis has successfully acquired initial data, and inversion of the data acquired during these initial tests has yielded satisfactory polarizabilities of a spherical target. In addition, precise positioning of the Rx assembly has been achieved via position inversion algorithms based solely on the data acquired from the receivers during the "on-time" of the primary field. Pedemis has been designed to be a flexible yet user friendly EMI instrument that can survey, detect and classify targets in a one pass solution. In this paper, the Pedemis instrument is introduced along with its operation protocols, initial data results, and current status. © 2012 SPIE.

Grzegorczyk T.M.,Delpsi LLC | Barrowes B.E.,U.S. Army | Shubitidze F.,Dartmouth College | Fernandez J.P.,Dartmouth College | O'Neill K.,U.S. Army
IEEE Transactions on Geoscience and Remote Sensing | Year: 2011

The simultaneous detection and identification of multiple targets using electromagnetic induction (EMI) time-domain sensors remains a challenge due to the fast decay of the magnetic field with sensor-target distance. For example, the signal from a weak yet shallow target or clutter item can overshadow that from a much larger yet deeper unexploded ordnance (UXO), potentially resulting in erroneous localization and/or identification. We propose, in this paper, a method based on the GaussNewton algorithm for the inversion of multiple targets within the field of view of sensors operating at EMI frequencies (tens of hertz to a few hundred kilohertz). In order to minimize the number of unknowns to invert for, the polarizability tensor is written as a time-independent orientation matrix multiplied by a time-dependent diagonal intrinsic polarizability tensor. Similarly, position is supposed to be time independent so that both position and orientation angles are inverted only once using all time channels collected by the instrument. Moreover, using the dipole approximation, we are able to compute the Jacobian in closed form for instruments with either square or circular primary field coils, thus contributing to the speed of the algorithm. Validating results are shown based on the measurement data collected with two EMI sensors on various types of UXO. © 2011 IEEE.

Grzegorczyk T.M.,Delpsi LLC | Fernandez J.P.,88 Franklin St Unit 301 | Shubitidze F.,Dartmouth College | O'Neill K.,U.S. Army | And 2 more authors.
Journal of Applied Geophysics | Year: 2012

Detection and classification of unexploded ordnance based on electromagnetic induction have made tremendous progress over the last few years, to the point that not only more realistic terrains are being considered but also more realistic questions - such as when to stop digging - are being posed. Answering such questions would be easier if it were somehow possible to . see under the surface. In this work we propose a method that, within the limitations on resolution imposed in the available range of frequencies, generates subsurface images from which the positions, relative strengths, and number of targets can be read off at a glance. The method seeds the subsurface with multiple dipoles at known locations that contribute collectively but independently to the measured magnetic field. The polarizabilities of the dipoles are simultaneously updated in a process that seeks to minimize the mismatch between computed and measured fields over a grid. In order to force the polarizabilities to be positive we use their square roots as optimization variables, which makes the problem nonlinear. The iterative update process guided by a Jacobian matrix discards or selects dipoles based on their influence on the measured field. Preliminary investigations indicate a fast convergence rate and the ability of the algorithm to locate multiple targets based on data from various state-of-the-art electromagnetic induction sensors. © 2012 Elsevier B.V..

Grzegorczyk T.M.,Delpsi LLC | Meaney P.M.,Dartmouth College | Meaney P.M.,Microwave Imaging System Technologies Inc. | Jeon S.I.,Electronics and Telecommunications Research Institute | And 3 more authors.
Biomedical Optics Express | Year: 2011

Microwave image reconstruction is typically based on a regularized least-square minimization of either the complex-valued field difference between recorded and modeled data or the logarithmic transformation of these field differences. Prior work has shown anecdotally that the latter outperforms the former in limited surveys of simulated and experimental phantom results. In this paper, we provide a theoretical explanation of these empirical findings by developing closed form solutions for the field and the inverted electromagnetic property parameters in one dimension which reveal the dependency of the estimated permittivity and conductivity on the absolute (unwrapped) phase of the measured signal at the receivers relative to the source transmission. The analysis predicts the poor performance of complex-valued field minimization as target size and/or frequency and electromagnetic contrast increase. Such poor performance is avoided by logarithmic transformation and preservation of absolute measured signal phase. Two-dimensional experiments based on both synthetic and clinical data are used to confirm these findings. Robustness of the logarithmic transformation to variation in the initial guess of the reconstructed target properties is also shown. The results are generalizable to three dimensions and indicate that the minimization form with logarithmic transformation offers image reconstruction performance characteristics that are much more desirable for medial microwave imaging applications relative to minimizing differences in complex-valued field quantities. © 2011 Optical Society of America.

Kemp B.A.,Arkansas State University | Grzegorczyk T.M.,Delpsi LLC
Optics Letters | Year: 2011

By considering a perfect reflector submerged in a dielectric fluid, we show that the Minkowski formulation describes the optical momentum transfer to submerged objects. This result is required by global energy conservation, regardless of the phase of the reflected wave. While the electromagnetic pressure on a submerged reflector can vary with phase of the mirror reflection coefficient between twice the Abraham momentum and twice the Minkowski momentum, the Minkowski momentum is always restored due to the additional pressure on the dielectric surface. This analysis also gives further evidence for use of the Minkowski stress tensor at the boundary of a dielectric interface, which has been the subject of a long-standing debate in physics and the source of uncertainty in the modeling of optical forces on submerged particles. © 2011 Optical Society of America.

Grzegorczyk T.M.,Delpsi LLC | Barrowes B.E.,Cold Regions Research and Engineering Laboratory
IEEE Transactions on Geoscience and Remote Sensing | Year: 2013

The current procedure to detect and identify unexploded ordnance (UXO) using electromagnetic induction (EMI) time-domain sensors is based on two steps. First, data are acquired over large areas in dynamic mode, and locations of interest are flagged based on measured field amplitudes. Second, sensors return to the flagged areas for more in-depth cued interrogation, providing high-quality data for subsequent identification and classification. Flagging based on field amplitude, however, has potential drawbacks: The magnetic field in the EMI regime exhibits a $1/R6 drop-off with range, and a deep UXO may not produce a strong response while still being potentially hazardous. To address this problem, we propose in this paper an inversion method based on Kalman and extended Kalman filters meant to do the following: 1) work with dynamic data; 2) provide both position and polarizability estimates; and 3) operate in real time (less than 100 ms in our case). Such full characterization of the target, albeit limited to within the 2.7-ms interrogation time window of the dynamic mode associated with the sensors studied here, provides useful information when deciding whether to continue with the cued interrogation. We validate the method for two popular EMI sensors, the second-version Man Portable Vector (MPV-II) and the MetalMapper, operated in very different settings: The MPV-II is used to interrogate a limited region of space atop a single target, whereas the MetalMapper is driven over long lanes along which several targets and clutter items are present. © 1980-2012 IEEE.

Grzegorczyk T.M.,Delpsi LLC | Barrowes B.E.,Cold Regions Research and Engineering Laboratory
IEEE Geoscience and Remote Sensing Letters | Year: 2014

The Pedemis sensor is a newly designed electromagnetic induction sensor that exhibits the unique characteristics of: 1) being able to physically decouple its transmitter and receiver modules and 2) offering the possibility of dynamically selecting various data acquisition modes (individual selection of transmitters and selection of data acquisition time for shallow/deep target interrogation). Such flexibility is expected to be instrumental in non-trivial terrains exhibiting either an abundant vegetation or being highly contaminated by large or dense clutter. Before validating the sensor in such challenging configurations, however, the Pedemis was taken to Aberdeen Proving Ground, MD, for its first test site validation. This letter presents the protocol adopted for data acquisition as well as inversion results on typical targets, including inversion of semi-synthetic data with up to five simultaneous targets. © 2013 IEEE.

Grzegorczyk T.M.,Delpsi LLC | Zhang B.,Lincoln Laboratory | Cornick M.T.,Lincoln Laboratory
IEEE Transactions on Geoscience and Remote Sensing | Year: 2013

We propose a two-pass ground-penetrating radar (GPR) approach to detect recently buried nonmetallic scatterers whose signals are otherwise undistinguishable from surrounding clutter. The operating framework is based on a pass-1 data collection over an object-free ground and a pass-2 data collection over the same ground, yet at unregistered positions, which may be contaminated by a recently implanted dielectric scatterer. The detection algorithm is based on a modified singular value decomposition approach and is shown to perform significantly better than a direct signal cancellation approach. Validating results are presented on measured target-free data to which synthetic targets of various strengths are added. Multiple realizations along the measurement path of the GPR array provide statistical diversity to the results which is cast as receiving operating curves, showing quantitatively the improved detection threshold of the new method. Copyright © 1980-2012 IEEE.

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