Position detection of unexploded ordnance from airborne magnetic anomaly data using 3-D self organized feature map

Tobely, Tarek El.; Salem, Abdelhamid Ben

doi:10.1109/isspit.2005.1577117

Cited by 18 publications

(9 citation statements)

References 14 publications

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“…A scanner moving in three dimensions with a KMZ51 magneto-resistive sensor is used to measure the magnetic anomaly created by the magnetic material whose magnetic characteristics is to be identified ( Fig. 2) [1][2][3][4][5][6][7][8][9][10][11][12]. The analog data (voltage) produced by the sensor is digitized by a 24-bit ADC (AD7714) and transferred to the computer for further processing (Fig.…”

Section: Measurement Systemmentioning

confidence: 99%

“…In the works, we have concentrated on the detection of improved and manufacturing-type steels with ferromagnetic characteristics widely used in industrial applications. The remote sensing is achieved by using a magnetic anomaly method [2][3][4][5][6][7][8][9]. The neural networks are extensively used for identification and classification purposes [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…The study presented here and the previous paper [1] is unique since reduced power consumption and highly accurate measurements can be achieved. Furthermore, this is a new approach for the identification of material with magnetic characteristics which can be achieved based on the detection of the vertical component of the Earth's magnetic field [5][6][7][8][9]. In addition, if the field lines of the Earth at a location where magnetic materials are found are constant and homogeneous, then it may give rise to some difficulties in identifying the material.…”

Section: Introductionmentioning

confidence: 99%

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Identification of materials with magnetic characteristics by neural networks

et al. 2012

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In industry, there is a need for remote sensing and autonomous method for the identification of the ferromagnetic materials used. The system is desired to have the characteristics of improved accuracy and low power consumption. It must also autonomous and fast enough for the decision. In this work, the details of inaccurate and low power remote sensing mechanism and autonomous identification system are given. The remote sensing mechanism utilizes KMZ51 anisotropic magneto-resistive sensor with high sensitivity and low power consumption. The images and most appropriate mathematical curves and formulas for the magnetic anomalies created by the magnetic materials are obtained by 2-D motion of the sensor over the material. The contribution of the paper is the use of the images obtained by the measurement of the perpendicular component of the Earth magnetic field that is a new method for the purpose of identification of an unknown magnetic material. The identification system is based on two kinds of neural network structures. The MultiLayer Perceptron (MLP) and the Radial Basis Function (RBF) network types are used for training of the neural networks. In this work, 23 different materials such as SAE/AISI 1030, 1035, 1040, 1060, 4140 and 8260 are identified. Besides the ferromagnetic materials, three objects are also successfully identified. Two of them are anti-personal and anti-tank mines and one is an empty can box. It is shown that the identification system can also be used as a buried mine identification system. The neural networks are trained with images which are originally obtained by the remote sensing system and the system is operated by images with added Gaussian white noises. © 2012 Elsevier Ltd. All rights reserved

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Section: Measurement Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identification of materials with magnetic characteristics by neural networks

et al. 2012

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“…This method can also be used for vehicle identification, traffic density observations, [11], geological studies [12], health [13], archeological investigations [14], mines, and buried explosives over the military zones [15], [16]. In recent years, the studies have been concentrated on the improvement of detection distances, accuracy, and power consumption.…”

Section: Introductionmentioning

confidence: 99%

“…This paper is unique since reduced power consumption and highly accurate measurements can be achieved. Furthermore, this is a new approach for the identification of material with magnetic characteristics which can be achieved based on the detection of the vertical component of the Earth's magnetic field [12]- [16].…”

Section: Introductionmentioning

confidence: 99%

Numerical Analysis for Remote Identification of Materials With Magnetic Characteristics

Ege

Şensoy

Kalender³

et al. 2011

IEEE Trans. Instrum. Meas.

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Abstract-There is a variety of methods used for remote sensing of objects such as acoustic, ground penetration radar detection, electromagnetic induction spectroscopy, infrared imaging, thermal neutron activation, core four-pole resonance, neutron backscattering, X-ray backscattering, and magnetic anomaly. The method that has to be used can be determined by the type of material, geographical location (underground or water), etc. Recent studies have been concentrated on the improvement of the criteria such as sensing distances, accuracy, and power consumption. In this paper, anomalies created by materials with magnetic characteristics at the perpendicular component of the Earth magnetic field have been detected by using a KMZ51 anisotropic magnetoresistive sensor with high sensitivity and low power consumption, and also, the effects of physical properties of materials on magnetic anomaly have been investigated. By analyzing the graphics obtained by 2-D motion of the sensor over the material, the most appropriate mathematical curves and formulas have been determined. Based on the physical properties of the magnetic material, the variations of the variables constituting the formulas of the curves have been analyzed. The contribution of this paper is the use of the results of these analyses for the purpose of identification of an unknown magnetic material. This is a new approach for the detection and determination of materials with magnetic characteristics by sensing the variation at the perpendicular component of the Earth magnetic field. The identification process has been explained in detail in this paper.Index Terms-Anisotropic magnetoresistive sensor (AMR), magnetic anomaly, magnetic materials, power consumption, remote sensing.

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