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Signal Processing Techniques for Landmine Detection Using Impulse Ground Penetrating Radar (ImGPR)

Tesfamariam, G. T. :
Signal Processing Techniques for Landmine Detection Using Impulse Ground Penetrating Radar (ImGPR).
[Online-Edition: http://tuprints.ulb.tu-darmstadt.de/3565]
TU Darmstadt
[Ph.D. Thesis], (2013)

Official URL: http://tuprints.ulb.tu-darmstadt.de/3565

Abstract

Landmines and unexploded ordinance (UXO) are laid during a conflict against enemy forces. However, they kill or maim civilians decades after the conflict has ended. There are more than 110 million landmines actively lodged in the globe. Every year more than 26,000 innocent civilians are killed or maimed. Most modern landmines are mainly nonmetallic or plastic, which are difficult to be detected using conventional metal detectors. Detection using hand-held prodding is a slow and expensive process. Impulse Ground Penetrating Radar (ImGPR) is a nondestructive technique capable of detecting shallowly buried nonmetallic anti-personnel (AP) and anti-tank (AT) landmines. In this PhD thesis, ImGPR is considered as a tool to detect landmines and UXO. The presence of strong ground clutter and noise degrade the performance of GPR. Hence, using a GPR sensor is almost impossible without the application of sophisticated signal processing.

In electromagnetic wave propagation modeling, a multilayer transmission line technique is applied. It considers different soil types at different moisture levels. Plastic targets of different diameters are buried at different depths. The modeled signal is then used to estimate the ground and buried target parameters. In a parameter estimation procedure, a surface reflection parameter method (SRPM) is applied.

Signal processing algorithms are implemented for clutter reduction and decision making purposes. Attention is mainly given to the development of techniques, that are applicable to real-time landmine detection. Advanced techniques are preceded by elementary preprocessing techniques, which are useful for signal correction and noise reduction. Background subtraction techniques based on multilayer modeling, spatial filtering and adaptive background subtraction are implemented. In addition to that, decorrelation and symmetry filtering techniques are also investigated.

In the correlated decision fusion framework, local decisions are transmitted to the fusion center so as to compute a global decision. In this case, the concept of confidence information of local decisions is crucial to obtain acceptable detection results. The Bahadur-Lazarsfeld and Chow expansions are used to estimate the joint probability density function of the correlated decisions. Furthermore, a decision fusion based on fuzzy set is implemented.

All proposed methods are evaluated using simulated as well as real GPR data measurements of many scenarios. The real data collection campaign took place at the Griesheim old airport and Botanischer Garten, Darmstadt, Germany in July 2011.

Item Type: Ph.D. Thesis
Erschienen: 2013
Creators: Tesfamariam, G. T.
Title: Signal Processing Techniques for Landmine Detection Using Impulse Ground Penetrating Radar (ImGPR)
Language: English
Abstract:

Landmines and unexploded ordinance (UXO) are laid during a conflict against enemy forces. However, they kill or maim civilians decades after the conflict has ended. There are more than 110 million landmines actively lodged in the globe. Every year more than 26,000 innocent civilians are killed or maimed. Most modern landmines are mainly nonmetallic or plastic, which are difficult to be detected using conventional metal detectors. Detection using hand-held prodding is a slow and expensive process. Impulse Ground Penetrating Radar (ImGPR) is a nondestructive technique capable of detecting shallowly buried nonmetallic anti-personnel (AP) and anti-tank (AT) landmines. In this PhD thesis, ImGPR is considered as a tool to detect landmines and UXO. The presence of strong ground clutter and noise degrade the performance of GPR. Hence, using a GPR sensor is almost impossible without the application of sophisticated signal processing.

In electromagnetic wave propagation modeling, a multilayer transmission line technique is applied. It considers different soil types at different moisture levels. Plastic targets of different diameters are buried at different depths. The modeled signal is then used to estimate the ground and buried target parameters. In a parameter estimation procedure, a surface reflection parameter method (SRPM) is applied.

Signal processing algorithms are implemented for clutter reduction and decision making purposes. Attention is mainly given to the development of techniques, that are applicable to real-time landmine detection. Advanced techniques are preceded by elementary preprocessing techniques, which are useful for signal correction and noise reduction. Background subtraction techniques based on multilayer modeling, spatial filtering and adaptive background subtraction are implemented. In addition to that, decorrelation and symmetry filtering techniques are also investigated.

In the correlated decision fusion framework, local decisions are transmitted to the fusion center so as to compute a global decision. In this case, the concept of confidence information of local decisions is crucial to obtain acceptable detection results. The Bahadur-Lazarsfeld and Chow expansions are used to estimate the joint probability density function of the correlated decisions. Furthermore, a decision fusion based on fuzzy set is implemented.

All proposed methods are evaluated using simulated as well as real GPR data measurements of many scenarios. The real data collection campaign took place at the Griesheim old airport and Botanischer Garten, Darmstadt, Germany in July 2011.

Uncontrolled Keywords: Signal processing techniques, landmine detection, ground penetrating radar(GPR), propagation modeling, transmission line approach, multilayer modeling, surface reflection method, reflection coefficient, transmission coefficient, ground parameter estimation, target parameter estimation, preprocessing, background subtraction, symmetry filtering, subtract and weight method, decision fusion, correlation coefficient
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Signal Processing
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications
Date Deposited: 11 Aug 2013 19:55
Official URL: http://tuprints.ulb.tu-darmstadt.de/3565
URN: urn:nbn:de:tuda-tuprints-35653
Referees: Zoubur, Prof. Dr.- Abdelhak M. and Mali, Prof. Dr. Dilip S.
Refereed / Verteidigung / mdl. Prüfung: 15 July 2013
Alternative Abstract:
Alternative abstract Language
Landminen und Blindgänger (UXO) werden während eines militärischen Konflikts gegen feindliche Kräfte vergraben. Allerdings töten oder verstümmeln sie Zivilisten Jahrzehnte nachdem der Konflikt beendet ist. Es gibt mehr als 110 Millionen aktive Landminen, die in der ganzen Welt verteilt sind. Jedes Jahr werden mehr als 26.000 unschuldige Zivilisten getötet oder verstümmelt. Die meisten modernen Landminen sind hauptsächlich nichtmetallisch bzw. aus Kunststoff, was eine Detektion mit herkömmlichen Metalldetektoren erschwert. Detektion mit in der Hand gehalten Stäben ist ein langsamer und teurer Prozess. Impuls Bodenradar (ImGPR) ist eine nicht-explosive Methode zum Aufspüren von flach begraben nichtmetallischen AntiPersonenminen (AP) und Anti-Panzer (AT) Landminen. In dieser Doktorarbeit wird ImGPR als ein Werkzeug betrachtet, um Landminen und Blindgänger zu erkennen. Das Vorhandensein starker Bodenechos und Rauschen, verringern die Leistung von GPR Geräten. Daher ist eine GPR-Sensor Benutzung fast unmöglich, ohne die Anwendung von geeigneter Signalverarbeitung. In dieser Arbeit wird die Übertragung elektromagnetischer Wellen modelliert durch eine mehrschichtige Übertragungsleitung. Dieses Modell beinhaltet verschiedene Bodenarten mit unterschiedlicher Feuchtigkeit. Kunststoff Ziele unterschiedlichen Durchmessers werden in unterschiedlichen Tiefen vergraben. Das modellierte Signal wird dann verwendet, um die Parameter des Bodens und des vergrabenen Zieles zu schätzen. Zur Parameterschätzung wird die Oberflächenreflexion-Parameter-Methode (SRPM) angewandt. Signalverarbeitungsmethoden zur Bodenechounterdrückung und Entscheidungsfindung wurden implementiert. Es wurde vor allem auf die Entwicklung von Techniken Wert gelegt, die für Echtzeit-Landminendetektion geeignet sind. Fortgeschrittene Methoden werden durch elementare Vorverarbeitungstechniken unterstützt, die nützlich für die Signal-Korrektur und Rauschreduzierung sind. Hintergrundsubtraktionstechniken, basierend auf Multilayer-Modellierung, räumliche Filterung und adaptive Hintergrundsubtraktion wurden implementiert. Außerdem wurden Dekorrelation und Symmetrie Filtertechniken behandelt. In der korrelierten Entscheidungsfusion werden lokale Entscheidungen zum Fusionszentrumübertragen, um eine globale Entscheidung zu treffen. In diesem Fall ist das Konzept der Vertrauensinformationen der lokalen Entscheidungen entscheidend um annehmbare Ergebnisse zu erhalten. Die Bahadur-Lazarfeld und Chow Erweiterungen werden verwendet, um die gemeinsamen Wahrscheinlichkeitsdichtefunktion der korrelierten Entscheidungen zu schätzen. Ebenfalls wurde Fuzzy-Set-basierte Entscheidungsfusion implementiert. Alle vorgeschlagenen Methoden wurden sowohl mit simulierten als auch mit echt gemessenen GPR Daten in vielen Szenarien evaluiert. Die Datenerhebungskampagne wurde in Griesheim am alten Flughafen und im Botanischen Garten, Darmstadt, Deutschland im Juli 2011, durchgef¨uhrt.German
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