Object Identification Using Multifrequency EMI Data

Keiswetter, Dean; Won, I. J.; Barrow, Bruce; Bell, Tom W.

doi:10.4133/1.2922673

Cited by 8 publications

(10 citation statements)

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“…In this case, the previously derived processor [as in (10)], which assumed a "fixed" target/sensor orientation, is not the optimal solution. Hence, in order to obtain the optimal discriminant function for the received data, the effect of these random factors must be integrated out, i.e., (11) where represents the height of the sensor from the target, and represent the horizontal position of the sensor relative to the center of the target, and are the a priori distributions of the position factors, and where is the model prediction (described in detail in Section III) of the th target response when it is located at the position ( ) relative to the sensor.…”

Section: Forward Model-based Bayesian Classifier Formulationmentioning

confidence: 96%

Classification of landmine-like metal targets using wideband electromagnetic induction

Gao

Collins²,

Geng³

et al. 1999

1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258)

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Abstract-In our previous work, we have shown that the detectability of landmines can be improved dramatically by the careful application of signal detection theory to time-domain electromagnetic induction (EMI) data using a purely statistical approach. In this paper, classification of various metallic landmine-like targets via signal detection theory is investigated using a prototype wideband frequency-domain EMI sensor. An algorithm that incorporates both a theoretical model of the response of such a sensor and the uncertainties regarding the target/sensor orientation is developed. This allows the algorithms to be trained without an extensive data collection. The performance of this approach is evaluated using both simulated and experimental data. The results show that this approach affords substantial classification performance gains over a standard approach, which utilizes the signature obtained when the sensor is centered over the target and located at the mean expected target/sensor distance, and thus ignores the uncertainties inherent in the problem. On the average, a 60% improvement is obtained.

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Section: Forward Model-based Bayesian Classifier Formulationmentioning

confidence: 96%

Classification of landmine-like metal targets using wideband electromagnetic induction

Gao

Collins²,

Geng³

et al. 1999

1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258)

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“…The features that are important in all sensing methods are low power consumption, low price, being unaffected by environmental changes, high precision, high reliability and stability. Some remote sensing methods used from past to present include electromagnetic induction (EMI) [1][2][3][4][5], ground effect radar (GPR) [6][7][8][9][10][11] and magnetic anomaly [12][13][14][15]18]. Magnetic anomaly is the most widely used remote sensing method due to its low price, low number of equipment and changeable sensitivity.…”

Section: Introductionmentioning

confidence: 99%

A Fluxgate Sensor Application : Coin Identification

Çıtak¹,

Çoramık²,

Ege³

2016

SIPIJ

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Today, coins are used to operate many electric devices that are open to the public service. Washing machines, play stations, computers, auto brooms, foam machines, beverage machines, telephone chargers, hair dryers and water heaters are some examples of these devices These devices include coin recognition systems. In these systems, there are coils at two different radius, which become electromagnets when the current is passed through them. The AC current supplied to the coils creates a variable magnetic field, which induces the eddy current on the coil during the passing of money. The magnetic field generated by the Eddy current reduces the current passing through the coil. The amount of change of current in the coil gives information about the coin; the type of metal (element) and the amount of metal (element). In this study, a new coin identification system (magnetic measurement system) is designed. In this system, the magnetic anomaly generated by the coin as a result of applying direct current to the coils is tried to be detected by fluxgate sensor. In this study, sensor voltages are acquired in computer environment by using developed electronic unit and LabVIEW based software. In the paper, experimental results have been discussed in detail.

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“…As attention has focused on it, suggestive studies have been performed and new instruments developed [1][2][3][4][5][6][7][8][9][10][11]. Unfortunately, omnipresent metallic clutter at UXO cleanup sites complicates matters because EMI devices are essentially metal detectors.…”

Section: Introductionmentioning

confidence: 99%

Data diversity for UXO discrimination in realistic settings with a handheld EMI sensor

O’Neill

Won

Oren

et al. 2004

Detection and Remediation Technologies for Mines and Minelike Targets IX

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(1) ERDC -CRREL, 72 Lyme Rd, Hanover NH 03755, Kevin.ONeill@ERDC.usace.army.mil ABSTRACT Electromagnetic induction sensing (EMI), between ~ 10's of Hz and 100's of kHz, may show the strongest promise for discrimination of subsurface, shallow metallic objects such as unexploded ordnance (UXO). While EMI signals penetrate the soil readily, resolution is low and responses are sometimes ambiguous. For crucial discrimination progress, maximum data diversity is desirable in terms of look angles, frequency spectrum, and full vector scattered field data. Newly developed instrumentation now offers the possibility of full vector UWB EMI data with flexible look angle and sensor distance/sweep, defined by precise laser positioning. Particulars of the equipment and resulting data are displayed. An indication is given of potential advantages for reducing the chronic ill-conditioning of inversion calculations with EMI data, when one takes advantage of the data diversity made possible by the instrumental advances. Some EMI measurement issues cannot be solved by EMI data diversity, as when small surface clutter above a much larger UXO effectively blinds an EMI sensor. EMI surveying must be supplemented by or sometimes replaced by ground penetrating radar (GPR) approaches in such instances.

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Object Identification Using Multifrequency EMI Data

Cited by 8 publications

References 0 publications

Classification of landmine-like metal targets using wideband electromagnetic induction

Classification of landmine-like metal targets using wideband electromagnetic induction

A Fluxgate Sensor Application : Coin Identification

Data diversity for UXO discrimination in realistic settings with a handheld EMI sensor

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