The intrinsic frequency dependence to electromagnetic induction (EMI) measurements of a metallic object depends on the size, shape, and metal type. This frequency dependence, referred to as the spectral response, can be exploited in identifying or classifying the object, as well as suppressing spurious EMI responses to geology. In order to acquire the necessary multi-frequency data, a sophisticated EMI sensor is needed.
The GEM-3 utilizes a continuous wave frequency-domain mode in which a hybrid current waveform is digitally generated containing energy at typically ten logarithmically spaced frequencies from a few hundred Hertz up to 48 kHz. The concentric-coil configuration suppresses the primary field at the receiver coil using a dual transmitter coil scheme. A digital Fourier transform is performed on the receiver coil emf at the selected frequencies, providing inphase and quadrature measurements.
The detection channel, selected from several options, combines the multi-frequency channels in a way that suppresses the response to magnetic soil and emphasizes metallic targets. Once a target is detected, the spectral character is compared to training data spectra stored in a library for the anticipated mines, and if the goodness-of-fit to the best matching library item is within a threshold, a mine is declared. The matching algorithm essentially compares the shape of the inphase and quadrature spectra, but modifications have been incorporated to account for amplitude reasonableness, to suppress noise induced from magnetic soil, and to allow for larger percentage errors for weak-response low-metal mines.
The Geophex GEM-3 sensor was tested at a government test site comprised of 980 1-m squares containing buried landmines and clutter (metallic debris). Electromagnetic (EM) induction spectroscopy (EMIS) was used to discriminate between the landmines and clutter items. Receiver-operator characteristics (ROC) were constructed based on the results of the analysis. Approximately 92% of the landmines were correctly identified as such, with a false alarm rate of 12%. In this report, we present a comparison of our identification results against the ground truth.
The EMIS method works well for high-metal mines for which the misfit threshold can be easily established, yielding a correct declaration in all cases without false alarms. For medium-metal mines, even though the misfit differences between the mines and clutter are not as clear as those for the high-metal mines, these mines were still identified at very low false alarm rates with the GEM-3 sensor. The low-metal mines may be discriminated from clutter if they yield reliable signals, but often at a much higher false alarm rate. The primary reason for this is that the EM signals from the low-metal mines are intrinsically weak and thus more subject to distortion by noise.
There are several possibilities for improving the low-metal mine identification, including (1) increasing the upper limit of the frequency band to obtain a stronger signal and better defined spectra; (2) decreasing the size of the sensing head to further localize the region of sensitivity of the sensor; (3) displaying the spectral curves and performing the identification in real time to allow operator inspection of the spectral match; and (4) defining a generalized misfit that incorporates signal amplitude and possibly other spectral features such as the quadrature peak.
Soil magnetic susceptibility is always greater than zero and is detectable using an electromagnetic (EM) induction sensor. When the frequency-domain EM response is affected by magnetic polarization, the in-phase component becomes negative at the low frequency and proportional to the ground magnetic susceptibility. The in-phase measurement can thus be used to compute the apparent magnetic susceptibility. This approach provides a means of detecting a buried object based on it susceptibility contrast to the host medium. For example, an M19 anti-tank mine is physically large (33cm×33cm×9cm) but has so little metal that metal detectors can miss it. When an M19 is buried in soil, it produces a cavity in magnetic susceptibility, which may be detected as a region of low or anomalous apparent susceptibility compared to the surrounding area. We derived a simple formula to compute the apparent magnetic susceptibility from the in-phase data at the resistive limit. The behavior of the apparent susceptibility for layered earth models has been studied using synthetic data. Apparent susceptibility anomalies may be predicted from these studies based on the susceptibility contrast, and geometry of the sensor and target. Finally, we present experimental data obtained using two sensors, a GEM-2 and a GEM-3.
We have designed and built a non-synchronous, sequential array of GEM-3 sensors for use with the Multi-sensor Towed Array Detection System (MTADS) with support from ESTCP. The roughly 2-m square array consists of three, 96-cm diameter GEM-3s in a triangular configuration. The GEM drive electronics have been modified to produce a substantially higher transmit moment, and thus increased sensitivity, than the standard GEM-3. The individual sensors transmit a composite waveform made up of ten frequencies from 30 Hz to 48 kHz for a single 1/30 s base period. Sequential operation allows two of these base periods for deconvolution and output of the frequency-dependent response from each GEM-3. After allowing for a short coil settling time between sensors, we achieve an array sampling rate of just over 9 Hz. Coupled with our standard survey speed of 3 mph, this results in a down-track sampling spacing of ~15 cm. The cross-track spacing is 50 cm. We have characterized these sensors at our Blossom Point test site. The static and dynamic response of the array to a variety of ordnance, ordnance simulants, and scrap is presented with consideration given to both detection and classification.
Although commercially available geophysical sensors are capable of detecting UXO at nominal burial depths, they cannot reliably discriminate between UXO and clutter. As a result, an estimated 75% of remediation funds are spent on nonproductive excavations. During the past few years, we have been studying the merits of using multifrequency EMI data for discriminating between UXO and non-UXO targets and believe the method has tremendous potential. The EMI spectral response of an object is a function of its electrical conductivity, magnetic permeability, shape, size, and orientation relative the primary exciting field. By measuring a target's spectral response, we obtain its characteristic frequency-dependent signature.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.