An algorithm is proposed to enumerate, locate and characterize individual signal sources given observation of their
combined signals. No a-priori estimate for the number of sources is required. We assume a forward model exists, and
that superposition holds, i.e. coupling between sources is ignored. A system of linear equations <i>y</i>=<i>Ax</i> is set up in which
columns of matrix <i>A</i> contain expected signals from a large number of hypothesized sources, and <i>y</i> contains the observed
signal. Recently-developed solvers designed for linear systems with sparse non-negative solutions make this approach
feasible even when large numbers of sources are involved. With each iteration, the collection of hypothesized sources is
refined using a Harmony Search algorithm. Application is demonstrated on the problem of locating multiple buried
conductors based on electromagnetic induction (EMI) signals observed at ground surface.
An object, made partly or wholly of metals, has a distinct combination of electrical conductivity, magnetic permeability, and geometrical shape and size. When the object is exposed to a low-frequency electromagnetic field, it produces a secondary magnetic field. By measuring the broadband spectrum of the secondary field, we obtain a district spectral signature that may uniquely identify the object. Based on the response spectrum, we attempt to 'fingerprint' the object. This is the basic concept of EMIS. From numerous surveys that we have conducted using our multifrequency electromagnetic sensors (GEM-2 and GEM-3), we have accumulated significant evidence that a metallic object undergoes continuous changes in response as the transmitter frequency changes. These observations made over may UXO targets suggest strongly that the EMI anomaly measured in a broad band offers an ability to both detect and identify a target. The frequency-dependent structure of the difference was also reproducible and consisting over a range of depths. Therefore, we have established that the FEM-3 is capable of delivering broadband EMI data with ample target-specific information content for the purpose of target classification and identification.
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.
The phenomenology of frequency- and time-domain electromagnetic induction (EMI) is examined in detail, through use of a rigorous electromagnetic scattering model, and through appropriate signal analysis. We demonstrate that both the time- and frequency-domain EMI signatures can be characterized in terms of a few magnetic singularities, thereby significantly reducing the number of features that need be stored for target identification. Further, we examine the aspect-dependent properties of the relative extinction strengths of the magnetic-singularity modes. Finally, we perform a statistical analysis of the relative efficacy of frequency- and time-domain EMI operation, for a class of conducting targets.
EMI sensors are used extensively to detect landmines. These sensors operate by detecting the metal that is present in mines. However, mines vary in their construction form metal- cased varieties with a large mass of metal to plastic-cased varieties with minute amounts of metal. Unfortunately, there is often a significant amount of metallic clutter present in the environment. Consequently, EMI sensors that utilize traditional detection algorithms based solely on metal content suffer from large false alarm rates. This false alarm problem can be mitigated for high-metal content mines by developing statistical algorithms that exploit models of the underlying physics. In such models it is commonly assumed that the soil has a negligible effect on the sensor response. To date, no testing has been done to validate the assumption that when modeling the response of EMI sensors to low-metal mines, the solid effects are negligible. In addition, advanced algorithms have not been applied specifically to the detection of low-metal mines. The Joint UXO Coordination Office (JUXOCO) is sponsoring a series of experiments designed to establish a performance baseline for EMI sensor. This baseline will be used to measure the potential improvements in performance offered by advanced signal processing algorithms. This paper describes the results of several experiments performed in conjunction with the JUXOCO effort. The results indicate that (1) the properties of the soil do affect the response of a broadband EMI sensor to low-metal mines, and (2) advanced algorithms can improve detection performance over traditional algorithms based solely on metal content.
A principal problem with traditional, narrowband EMI sensors involves target identification. As a consequence, in minefield or unexploded ordinance (UXO) detection, for example, each piece of buried metal must be excavated, causing significant false alarms in regions littered with anthropic clutter. Therefore, the principal challenge for the next generation of EMI sensors is development of electronics and algorithms which afford discrimination. To this end, in this paper we operate in the frequency domain, considering wideband excitation and utilize the complex, frequency-dependent EMI target response as a signature. To test the signature variability of different metal types and target shapes, as well as for calibration of an actual sensor, we have developed a full-wave model for the analysis of wideband EMI interaction with highly (but not perfectly) conducting and permeable targets. In particular, we consider targets which can be characterized as a body of revolution, or BOR. The numerical algorithm is tested through use of a new wideband EMI sensor, called the GEM-3. It is demonstrated that the agreement between measurements and theory is quite good. Finally, we consider development of signal processing algorithms for the detection and identification of buried conducting and permeable targets, using wideband data. The algorithms are described and then tested on data measured using the GEM-3, with results presented in the form of contour plots as a function of the number of discrete frequencies employed.
An object, made partly or wholly of metals, has a distinct combination of electrical conductivity, magnetic permeability, and geometrical shape and size. When the object is exposed to a low-frequency electromagnetic field, it produces a secondary magnetic field. By measuring the secondary field in a broadband spectrum, we obtain a distinct spectral signature that may uniquely identify the object. Based on the response spectrum, we attempt to 'fingerprint' the object. This is the basic concept of Electromagnetic Induction Spectroscopy (EMIS). EMIS technology may be particularly useful for detecting buried landmines and unexploded ordnance. By fully characterizing and identifying an object without excavation. We should be able to reduce significantly the number of false targets. EMIS should be fully applicable to many other problems where target identification and recognition (without intrusive search) are important. For instance, an advanced EMIS device at an airport security gate may be able to recognize a particular weapon by its maker and type.
A new, monostatic, broadband, electromagnetic sensor, known as the GEM-3M, has been prototyped and tested at various sites containing buried unexploded ordnance and mines. The instrument consists of a pair of concentric, circular coils that transmit a continuous, broadband, digitally controlled, electromagnetic waveform. The two transmitter coils, with precisely computed dimensions and placement, create a zone of magnetic cavity at the center of the two coils. A third receiving coil is placed within this magnetic cavity such that it senses only the weak, secondary field returned from the earth and buried target(s). The mine detector is designed for ordinary soldiers, and, when completed, will have the following unique features: (1) one-man portable high-tech mine detector: intelligent, realtime data interpretation and display on a color LCD screen; (2) targets can be metallic mines, nonmetallic mines, or a disturbed soil condition; (3) detection and characterization based on visual color displays, rather than the tonal changes common to current metal detectors; (4) broadband; selectable frequencies for depth scanning suitable for regional soil conditions and geology, and; (5) all sensor coils housed in a light, circular disk - very similar in appearance to a conventional metal detector.