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18th EEGS Symposium on the Application of Geophysics to Engineering and Environmental Problems
- Conference date: 03 Apr 2005 - 07 Apr 2005
- Location: Atlanta, Georgia, USA
- Published: 03 April 2005
21 - 40 of 146 results
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Broadband Electromagnetic Detection and Discrimination of Underwater Uxo
Authors Bill SanFilipo, Steve Norton and I.J. WonThe electromagnetic induction (EMI) response to metal objects in the marine environment,
including UXO and clutter, is significantly altered by the conductive seawater. Two effects can be
observed – propagation effects associated with the seawater skin depth that attenuate and phase rotate
the response, and the addition of the response associated with the perturbation of the flow of currents
induced in the surrounding water, referred to as the current channeling response (CCR). These effects
distort the multi-frequency spectral response of the target from the normal free-air eddy current response
(ECR, including magnetic polarization for ferrous targets).
If the spectral character is used to classify or identify the target, these effects must either be
incorporated into the model or library used as the reference, or they must be minimized so that they can
be ignored. Since the relative amplitude of the CCR to ECR depends on variable conditions, including
sensor-target geometry, seawater salinity, and the surface condition of the target (paint or corrosion can
result in a negative CCR by forcing background currents around the target), explicitly accounting for
CCR is difficult and subject to knowledge of these variables. Accounting for propagation effects also
depends on knowledge of sensor-target distance. Thus, restricting operational parameters to minimize
the effects of the seawater may be the most straightforward and reliable approach.
In order to quantify the CCR and propagation effects over the full range of operational
parameters, we have developed some analytical models for special cases and we have performed
controlled underwater experiments with spheres to compare with the sphere models, and UXO
surrogates (pipes). Another algorithm that we developed is the perfectly conducting or insulating
spheroid in a conductive medium, which helps quantify the effect of aspect ratio and orientation on CCR
and ECR at the inductive limit and for insulated targets.
As a preliminary test on the potential application of EMI based discrimination, we have
performed our simple single-point spectral matching algorithm on underwater data using a free-air
library. By limiting the frequency range to 12 kHz, and target-sensor geometries to ranges with high
signal/noise (inherently limits lateral offset distances), the ECR dominates over CCR, and propagation
effects are not too great (wave induced noise also is less at lower frequencies). Under these constraints,
the matching algorithm performance is reasonably effective at identifying the target for a small suite (5)
of items in the library. Identifying clutter, based on goodness-of-fit, is more difficult, but will work for
many clutter items.
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Detection of Uxo and Landmines Using 2-D Modeling of Geoelectrical Resistivity Data
Authors Gad El-Qady and Keisuke UshijimaBuried landmines pose serious hazard in more than 60 countries across the globe. Recent
estimations suggest as many as 110 million such objects lay worldwide. Detecting these mines with
standard metal detectors is difficult, as many are comprised primarily of plastic, with often only a firing
pin as the sole metallic component. The development of geophysical methods for unexploded Ordnance
(UXO) detection has been underway for almost ten years, and arose in the international context from the
need to rapidly characterizing large areas of potentially UXO-contamination.
In this work, the geoelectrical resistivity could be one of the most useful parameters to
discriminate ordnance types, shapes and locations especially near the surface. This study represents a
successful trial to adopt the geoelectrical resistivity technique for detecting buried UXO and other clutter
environmental noise. A forward and inversion routine had been adopted and applied to synthetic
resistivity models for different UXO and landmines. In addition, models of non metal ordnance had been
used, and were successfully detected. The obtained results show high efficiency of the technique to
image those models. Now we are trying to adopt the technique to work in the filed, hence apply it for
test site.
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Automatic Detection of Uxo Anomalies Using Extended Euler Deconvolution
Authors Kris Davis, Yaoguo Li and Misac NabighianThe paper presents an algorithm for automatic detection of UXO anomalies in total-field
magnetic data based on the concept of structural index (SI) of a magnetic anomaly. The magnetic
field produced by a dipole-like, source such as a UXO, varies with inverse distance cubed and
therefore has an SI of 3. Identifying magnetic anomalies having structural indices of 3 enables direct
detection of potential UXO targets. The recently developed Hilbert based extended Euler
deconvolution method (Nabighian and Hansen, 2001) provides an efficient means for calculating the
SI by utilizing the Euler equations for the two components of 3D Hilbert transform. We first perform
extended Euler deconvolution to compute SI as a function of position and window size. At each
location, we examine the Euler solutions from different window sizes and identify the ones whose SI
is within a small tolerance of 3. Existence of such a solution indicates the presence of a potential
UXO target.
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Processing and Inversion of Magnetic Gradient Tensor Data for Uxo Applications
Authors Vinicio Sanchez, David Sinex, Yaoguo Li, Misac Nabighian, David Wright and David vonG SmithWe present a set of techniques for processing and inverting multi-component magnetic gradient
data for UXO detection and discrimination. A magnetic gradiometer for the UXO application, developed
jointly by US Geological Survey and Colorado School of Mines, measures the full gradient tensor of a
magnetic field. In contrast to total-field intensity measurements, gradient data have the advantage that
they are less affected by common-mode noise and may carry more useful information about subsurface
targets. Multiple tensor components also enable the extraction of a coherent common signal to further
increase the signal-to-noise ratio. The increased data quality opens new avenues for developing novel
approaches to UXO detection and discrimination. We have examined two different processing methods
based on the inherent relationship among the multiple tensor components, and we have developed an
inversion algorithm for recovering dipole and quadrupole source parameters from tensor data. We
outline these algorithms and illustrate the advantages of gradient data over total-field measurements.
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Travel Time Tomography Using Frequency Responses Collected By Cwr Experimentation
Authors Mohammad Farid, Akram N. Alshawabkeh and Carey M. RappaportDetecting and imaging dense non-aqueous phase liquids (DNAPLs) in the subsurface is a challenging problem that is of interest to the Department of Energy, Department of Defense, and several local and state agencies. Current DNAPL detection techniques, such as Direct Push Probe Technologies (DPT) and In-Situ Tracers (IST) have risks and limitations. Cross-well radar (CWR) is a radar-based geophysical technique with low invasiveness for real time monitoring of DNAPLs. This technique uses electromagnetic waves transmitted and received through antennas in the subsurface. The computerized tomography is applied to a pilot-scale experimental facility constructed by the authors (referred as SoilBED) in this research. Cross-tomography data at multiple depths and locations were collected to simulate a 1/100 scaled contaminated soil problem. The experimental results are converted to the time domain signals. The resulting signal travel times are compared with the simulated results by FDTD. The transformed signals are used to prepare signal intensity and travel time tomograms of the SoilBED cross-sectional slices, for background and scattered field to study the signature of the scatterers. The results are able to visualize the dielectric objects in the saturated soil.
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Soil /Metal Discrimination Analysis of EM 61 Mk Ii Time Decay Response at former Camp Croft, Sc
Electromagnetic (EM) data recently acquired for a munitions detection project, processed using
standard Geosoft Oasis Montaj methods and analyzed in profile, produced more than 1000 targets per
acre, far more than the number predicted by prior clearance in adjacent areas.
Standard data processing was expanded to incorporate a new technique developed by
Geophysical Associates (GPA) for dealing with magnetic soils in Hawaii. This technique is GPA
Soil_Metal Discrimination Analysis, based on statistical Chi-squared discrimination analysis of the
difference of time decay response across the four EM61 Mk II channels from that of soil and rocks.
Preliminary results show that GPA Soil_Metal Discrimination Analysis reduced the number of
targets per acre by approximately 80%. Most of the GPA-derived targets yielded significant metal
items.
As in other geophysical approaches, there remains some residual risk that not all buried
munitions will be detected. Some metallic objects, at certain orientations, have decays similar to
magnetic soil and will yield corresponding Chi-squared results.
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Application and Extension of Texture Feature Coding Methods To Anti-Tank Landmine Detection
Authors Peter Torrione and Leslie CollinsRecent advances in ground penetrating radar (GPR) fabrication and related signal processing have
yielded robust performance on government sponsored blind tests of anti-tank landmine detection
capabilities on test lanes. Recent data collections with the NIITEK GPR system have focused on more
difficult “off-lane” soil conditions that typically contain higher levels of sub-surface GPR anomalies and
provide more difficult tests of anti-tank target detection capabilities. Our recent research in this field has
focused on the application of advanced signal processing techniques to target/clutter discrimination at
pre-screener-flagged locations of interest. In this work we discuss the applications and extensions of a
texture feature coding method (TFCM) for landmine detection in off-lane soils. First we consider
application of the TFCM technique to target detection in 2-D GPR data slices. We also consider
application of the TFCM to “tiled” images containing multiple instantiations of a target response.
Finally we consider a 3-D extension of the TFCM and apply our extension to target detection in 3-D
time-domain GPR data. Our results indicate performance increases for TFCM-based processing of prescreener
generated alarms, with the most robust performance increases resulting from application of our
3-D TFCM extension.
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Multisensor, Remotely-Operated force Protection Mine Detection
Authors Gregory M. Schultz, Karen Norris Zachery and Leslie M. CollinsDespite improvements in both military and civilian mine detection equipment, humanitarian
demining remains a slow, hazardous, and labor-intensive task. The Force Protection Demining System
(FPDS) seeks to provide an efficient and reliable, teleoperated, mine detection platform to eradicate
explosive ordnance and allow reoccupation of mined areas by local inhabitants. The FPDS is equipped
with electromagnetic induction (EMI) and ground penetrating synthetic aperture radar (GPSAR) sensor
arrays integrated onto a remote-controlled, rubber-tracked vehicle. The multi-sensor detection system
fuses source sensor data and/or extracted sensor information to provide an increased level of mine
detection while minimizing false alarms. Extensive preliminary testing at test facilities yields results
that define system integration issues and constrain detection performance for each sensor array. An
important focus of our testing is the characterization of signal-, image-, and physics-based features used
in discriminating targets from clutter. Acquisition of independent and dual-mode data collected over
simulants, landmines, and UXO facilitates the development of a preliminary library of system target
responses from which optimal features are determined. The developed detection software system also
exploits spatial registration and multi-sensor data fusion algorithms to provide real-time automatic target
recognition information to the user.
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A Multisensor System for The Detection and Characterization of Uxo
Authors Alex Becker, Erika Gasperikova, H. Frank Morrison and J. Torquil SmithA prototype active electromagnetic system has been developed for detecting and characterizing
UXO. The system employs two orthogonal vertical loop transmitters and a pair of horizontal loop
transmitters spaced apart vertically by 0.7 m. Eight vertical field detectors are deployed in the plane of
each of the horizontal loops and are arranged to measure offset vertical gradients of the fields. The
location and orientation of the three principal polarizabilities of a target can be recovered from a single
position of the transmitter-receiver system. Further characterization of the target is obtained from the
broadband response. The system employs a bipolar half sine pulse train current waveform and the
detectors are dB/dt induction coils designed to minimize the transient response of the primary field
pulse. The target transient is recovered in a 40 μsec to 1.0 msec window. The ground response imposes
an early time limit on the time window and system/ambient noise limits the late time response.
Nevertheless for practical transmitter moments and optimum receivers the size and the ratio of
conductivity to permeability can be accurately recovered. The prototype system has successfully
recovered the depths and polarizabilities of ellipsoidal test targets.
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The Advanced Ordnance Locator (AOL): A Dual-Mode Tem and Magnetics System for Detection and Classification of Uxo
Authors D.D. Snyder and D.C. GeorgeWith funding from NAVEODTECH (Indian Head, MD), Blackhawk GeoServices is
collaborating with G&G Sciences and Geometrics to assemble and test a dual-mode system for ordnance
location combining a multi-sensor, multi-component TEM system with a total field magnetic
gradiometer. The new sensor array is integrated with an efficient computer-controlled transmitter and a
high-speed multi-channel (28-channel, 800 kilosample/sec) data acquisition system. The resulting
system has unprecedented capability and flexibility for the study, in particular, of the performance of
TEM systems and the noise that affects them. In this paper, we describe our dual-mode system and
present results from both local tests and tests at the Navy’s Baseline Ordnance Classification Test Site
at Blossom Point, MD. We compare data from our TEM system with the Naval Research Laboratory’s
man-portable MTADS and other systems as a baseline. Subsequent to our Blossom Point
demonstration, we experimented with alternative transmitter waveforms in an effort to improve the
signal to noise ratio (SNR) for detection. Our results demonstrate that the AOL system has a
significantly better SNR for detection during dynamic surveys than the other baseline systems with
which we compared. We attribute this improved performance to careful design of system components
together with an appropriate choice of the current waveform parameters (e.g., base period, pulse
polarity, etc) for dynamic data acquisition.
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Multi-Sensor Uxo Detection System
Authors Noel T. Rogers, Stewart K. Sandberg and H.H. BennettA multi-sensor unexploded ordnance (UXO) detection system has been developed in which the
various sensors have been positioned in very close proximity to one another. This system is capable of
simultaneously deploying magnetic and electromagnetic sensors, along with real-time decimeter GPS
positioning, and real-time data monitoring by a single operator.
In one mode of operation, a Geonics EM-63 electromagnetic system is deployed along with a
Gem Systems GSMP-40 optically-pumped potassium vapor magnetometer. In this mode, the distance
between these two sensors on a rigid platform is approximately 1.5 meters. Positioning coordinates,
obtained in real-time, are accurate at the decimeter scale, using a NavCom SF-2050M GPS receiver,
which utilizes the StarFire satellite-based augmentation system (SBAS). Data from the electromagnetic,
magnetic, and positioning systems are recorded in a laptop computer in real-time, and available on a
visual display as profile data plots, and tracking using a map-type display.
Electromagnetic and magnetic sensor placement in close proximity is achieved using a secondary
electromagnetic transmitting coil operating in tandem with the Geonics EM-63. The magnetic sensor is
placed at a null point of the total primary magnetic field generated from the EM-63 transmitter coil and
the secondary coil combination. Magnetic field mapping in the vicinity of these coils was accomplished
using a magneto-resistive chip, which provided several candidate null positions. Extensive testing of the
effect of the secondary transmitter coil on anomalies over known UXO targets provided refinement of
the sensor placement. The result of this work is that the sensor platform configuration produces a
distortion of total magnetic field intensity anomaly measurements less than 10%. Anomaly shape is
only affected to a minimal degree, allowing confidence in resulting computer modeling of these data for
target geometry, and hence discrimination.
Field testing of the platform and sensors took place at two locations near Albuquerque, New
Mexico, and at the U.S. Army Corps of Engineers UXO test bed in Vicksburg, Mississippi. The
instrument platform proved to be robust in these field-scale tests, and the value of multi-sensor datasets
was apparent upon analyses of these data.
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Digital Geophysical Mapping In Wooded Conditions Using An Integrated Em61 Mkii and Robotic Total Station Navigation Vehicular-Towed Deployment System
Authors Martin J. Miele, Ji Ma, Sandra A. Takata, John P. Dolynchuk, Mark Sellers and Larry FowlerShaw Environmental Inc., (Shaw), is conducting digital geophysical mapping (DGM) at the
Former Conway Bombing and Gunnery Range (Conway), Myrtle Beach, SC, using an array of 2 EM61-
MKIIs integrated with a Leica Robotic Total Station (RTS) navigation system towed behind a John
Deere Gator. The site is over 900 acres of Carolina Forest vegetation ranging from rows of trees to
densely wooded areas with interspersed wetlands. The performance objective is to locate all detectable
unexploded ordnance (UXO) items (including 50 mm) to a depth of 4 feet below the surface. This
project is the first high-volume munitions of concern (MEC) survey conducted under these challenging
site conditions using high-tech methodologies.
Given the size of this effort, high-productivity acquisition of high-fidelity data is key to this
project. The survey results show that this deployment is able to detect and characterize 50 mm (and
larger) UXO and UXO-like items with accurate target location in the wooded areas where global
positioning systems (GPS) are in-operable.
This case study discusses the challenges of high-productivity deployment systems in wooded
conditions. Additionally, it demonstrates that aggressive data collection using stable deployment
systems results in both superior quality and cost effective DGM projects.
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A Simple Magnetic Charge Model for Classification of Multiple Buried Metallic Objects In Cases With Overlapping Signals
Authors Fridon Shubitidze, Kevin O’Neill, Irma Shamatava, Keli Sun and Keith PaulsenThis paper presents an application of a simple surface magnetic charge model to discriminate
between objects of interest such as unexploded ordnance (UXO) and innocuous items, in cases when
signals from buried objects are a mixture of responses from two or more items. In the low frequency
(ten’s of Hertz up to several hundred’s of kHz) electromagnetic induction (EMI) sensing considered
here, both conduction and displacement currents may be neglected within the medium surrounding a
metallic object. Therefore, the scattered magnetic field outside the object is represented in terms of
scalar potential fields, from which one can obtain all scattered magnetic fields. While these are time
dependent by virtue of forcing functions or boundary conditions, they correspond in structure to static
fields. Such fields are appropriately, and readily, produced mathematically by equivalent elementary
magnetic charges placed on a convenient fictitious closed surface [1, 2, 3]. This forward model is
physically complete in the sense that all heterogeneity, near and far field, and internal interaction effects
within the object are included. It is very fast; in particular it can be implemented in inversion
calculations on a PC. According to the Gauss’s law,∇⋅B=ρeq , the net flux of magnetic field through any
closed surface equals the total (equivalent) magnetic charge ρeq inside the surface. The frequency
spectrum of this total induced equivalent charge is used here as a discriminant. Based on measured data
from two scatterers together, an iterative two step procedure is used in conjunction with the differential
evolution (DE) algorithm [4, 5]. One step determines of each object’s location and orientation and the
other determines the amplitudes of the responding fictitious magnetic charges. Once the objects are
isolated, the total magnetic charge for each is calculated as a function of frequency and compared to
cataloged/library data. Finally, blind classification analyses are performed for a single object as well as
for multiple subsurface scatterers, when two objects appear simultaneously within the field of view of
the sensor.
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An Empirically Based Ellipsoidal Model for Multiple Frequency Emi Signatures From Uxo
Authors Bruce Barrow, Nagi Khadr, Jonathan Miller and Herbert H. NelsonEfforts to model electromagnetic induction (EMI) signatures from unexploded ordnance (UXO)
have focused on the magnetic polarizability constants that characterize the dipole response of the UXO
along its axes. These polarization factors are a function of time or frequency depending on the EMI data.
While these curves can be analytically modeled in terms of size and composition for simple shapes like
spheres, an analytic representation for the response from general objects has proven elusive.
Functional forms have been found that fit polarization response functions for a wide variety of
objects. One such form is presented here in the frequency domain. This matches the analytic cases for
both a sphere and an infinite cylinder in the high permeability limit. The parameters for this empirical
function can be related to the demagnetization and time constants, as well as the volume, of the object.
For the case of an ellipsoid, the demagnetization constants and volume are analytically well-defined,
while the time constants are not. Here, we assume the time constants to scale as the ellipsoid dimensions
squared. While this assumption is a weak one, data inversions will be presented that return consistent
size dimensions for a given UXO item.
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Decay Time Constant Analysis for Uxo Target Prioritization
Authors Bart G. Hoekstra, Amy Walker and Andrew SchwartzThe Geonics EM-61MK2 is currently used for many surveys for UXO detection. The system has
the capability to record the voltage over four different times after current turn off in the
transmitter/receiver coil. This allows the computation of the time constant of decay between these four
channels and the possibility that this additional information could be used to prioritize geophysical
anomalies for intrusive investigation. Previous work has demonstrated that the four time gates are
located too soon after the current turn-off to perform an inversion capable of characterizing the buried
objects in terms of its size, shape, depth and composition. This paper will analyze the potential for the
apparent time constant to prioritize the geophysical anomalies and reduce the number of anomalies that
are intrusively investigated, by lowering the priorities of anomalies that have clearly different
characteristics from the objects of interest.
This paper will focus on geophysical surveys conducted for the Chemical Warfare Materiel
(CWM) Scoping and Security Study for the purposes of detecting steel Chemical Agent Identification
Sets (CAIS) shipping containers. There objects are larger and heavier than typical munitions and
explosives of concern (MEC) items and thus offer a better opportunity to prioritize target selection.
Additional data from test are also discussed in this paper.
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Support Vector Machines for EM Data Interpretation
Authors Heidi Anderson Kuzma and James W. RectorSupport Vector Machines (SVMs) are a class of trained algorithms which were introduced in the
mid-1990s which have rapidly reproduced state-of-the-art computer learning results. They are much
easier to understand than neural networks because they mimic the natural way that geophysicists think.
Using examples of objects and associated synthetic electromagnetic signatures, an SVM can be trained
to find the conductivity of similar objects from new EM signatures. Normally such an operation would
fall under the domain of geophysical inversion. SVMs do it in a way that is much more akin to
interpolation, producing values for the thickness of a spherical shell based on the similarity of its
signature to the training signatures. An SVM can iinterpret a signature with an accuracy of 10% or
better. The technique is general enough to apply to a wide variety of geophysical inverse problems.
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Uxo Discrimination Using Blind Source Separation
Authors Yingyi Tan, Stacy L. Tantum and Leslie M. CollinsStatistical signal processing techniques have shown progress in discriminating UXO from clutter
when the objects occur in isolation. Under this condition, only a single object contributes to the sensor
measurement. For multiple closely-spaced subsurface objects, however, the unprocessed sensor measurement
is a mixture of the responses from several objects. Consequently, the unprocessed measurements
cannot be used directly to discriminate UXO from clutter. In this paper, we implement blind source separation
(BSS) techniques, specifically independent component analysis (ICA), to recover the unobserved
object signatures from the mixed measurement data obtained by electromagnetic induction (EMI) sensors,
and then use the recovered signatures for UXO/clutter discrimination. Discrimination performance
depends on multiple factors, including the number of clutter objects in proximity to the UXO and the
separation distance between the UXO and clutter. Simulation results are presented illustrating the impact
of these factors on discrimination performance.
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Synthetic Crosshole Tomography Studies of Bridge Foundation Sites in Karst Terrane
Authors Dennis R. Hiltunen and Gye-Chun ChoSeismic crosshole tomography systems for characterization of the subsurface at bridge sites in mantled karst terrane were evaluated in this study. There is great need for a reliable testing method to map competent rock and estimate pile tip elevations during design of a structure. Prior to conduct and detailed analysis of crosshole tests at actual bridge sites in karst, important “synthetic model” investigations were first undertaken. For purposes herein, “synthetic models” refer to earth models whose velocity profile is assumed or known a priori. The synthetic model studies conducted indicate that the crosshole system is capable of accurately identifying and delineating horizontal and slanted layer interfaces, and that the method can produce valuable information for subsurface profiles that include dropping and pinnacled interfaces, and anomalies such as boulders or cavities. Based upon these findings, it can be concluded that seismic crosshole appears to be technically feasible for developing basic layer structure and top of rock profile in karst terrane.
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Meeting Tighter Navigation and Data Qc Requirements for Mec Investigations
Authors Kent Boler, Martin Miele, Ji Ma and Richard GrabowskiCurrently, good DGM implementation for MEC can get 1 to 2-ft radii navigational accuracies
during production and better during demonstration surveys. The differences between a 1-ft and a 2-ft
implementation are the selection of appropriate navigation systems, up-front thought in survey design,
and rigorous QC including inspections, audits, and failure analysis.
At two sites at the former Seneca Army Depot, where the performance objective was to detect
small (down to 20mm) target items, Shaw Environmental (Shaw) used an EM-61MK2 towed array with
robotic total station navigation that reliably got close to 1-ft total positional error site-wide. Keys to the
implementation included optimization of the form factor (deployment system and geometry) to
minimize bounce, pitch, roll, and yaw, software and logger selections to minimize latency issues, and
establishment of many QC control points.
The volume of DGM production data, QC data, QC assessments, and documentation can be
overwhelming. Although fixed calibration site data were good indicators of field data quality, the most
time efficient indicators of positional data quality were known location QC points.
The operational demands of navigation, logging, and monitoring multiple simultaneous data
streams on the equipment operators are a challenge. Audits and failure analysis are performed to ensure
compliance with operating procedures and, equally important, to optimize those procedures to minimize
the potential for incidental or catastrophic errors.
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The Effects of Speed and Platform Stability On Em61 Mk2 Anomaly Responses
Authors Andrew B. Schwartz and Amy N. WalkerThe U.S. Army Engineering & Support Center, Huntsville collected and evaluated EM61
MK2 electromagnetic data over a controlled test site using five different platforms, each
deployed multiple times at different tow speeds. We evaluated the effects of sensor speed on the
noise levels and peak anomaly amplitudes of measured EM data and we evaluated the effects of
different tow platforms on both background and anomaly responses. We analyzed our data to
derive background noise statistics for each dataset, anomaly peak responses corrected for
background noise, the spatial extent of anomalies, and anomaly signal to noise ratios.
We found that background noise increases as tow-speeds increase. With few exceptions,
anomaly peak responses and SNRs decreased as the tow speed was increased. On average, the
data show that the spatial extent of anomalies increased as tow speed increased. Our results
suggest that improvements to platform stability result in lower background noise levels and
increased SNRs. We also found that the background noise and anomaly responses increased
when the sensor height above the ground was reduced.
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