Persistent Link:
http://hdl.handle.net/10150/195341
Title:
Enhanced Detection of Ground Targets by Airborne Radar
Author:
Bruyere, Donald Patrick
Issue Date:
2008
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
This dissertation deals with techniques that enhance the detection of ground targets by airborne radar. The methods employed deal with the problem of air to ground detection by breaking the problem into two broad categories. The first category deals with improving detection of moving targets by using space-time adaptive processing (STAP) in a multistatic configuration. Mult-static STAP provides increased detection performance by observing targets from multiple perspectives. Multiple viewing perspectives afford more opportunities to the combined system for observing radial velocity of the target more directly, thus increasing Doppler that helps distinguish the target from background clutter. Detection performance also improves through an increased number of independent observations of a target, which reduces the likelihood of the target fading for the combined system. Increasing detection performance by increasing the number of independent observations is referred to in communications theory as channel diversity. The second part of this dissertation deals with the problem of distinguishing stationary targets from background clutter within a Synthetic Aperture Radar image. Stationary target discrimination is accomplished by exploiting the statistical nature of multifaceted metallic objects within a scene. The performance improvement for both moving and non-moving improvement methods is characterized and compared to other systems that attempt to accomplish the same end using different means.
Type:
text; Electronic Dissertation
Keywords:
STAP; Multistatic; radar; ATR; adaptive processing; signal processing; detection
Degree Name:
PhD
Degree Level:
doctoral
Degree Program:
Electrical & Computer Engineering; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Goodman, Nathan; Melde, Kathleen
Committee Chair:
Goodman, Nathan; Melde, Kathleen

Full metadata record

DC FieldValue Language
dc.language.isoENen_US
dc.titleEnhanced Detection of Ground Targets by Airborne Radaren_US
dc.creatorBruyere, Donald Patricken_US
dc.contributor.authorBruyere, Donald Patricken_US
dc.date.issued2008en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThis dissertation deals with techniques that enhance the detection of ground targets by airborne radar. The methods employed deal with the problem of air to ground detection by breaking the problem into two broad categories. The first category deals with improving detection of moving targets by using space-time adaptive processing (STAP) in a multistatic configuration. Mult-static STAP provides increased detection performance by observing targets from multiple perspectives. Multiple viewing perspectives afford more opportunities to the combined system for observing radial velocity of the target more directly, thus increasing Doppler that helps distinguish the target from background clutter. Detection performance also improves through an increased number of independent observations of a target, which reduces the likelihood of the target fading for the combined system. Increasing detection performance by increasing the number of independent observations is referred to in communications theory as channel diversity. The second part of this dissertation deals with the problem of distinguishing stationary targets from background clutter within a Synthetic Aperture Radar image. Stationary target discrimination is accomplished by exploiting the statistical nature of multifaceted metallic objects within a scene. The performance improvement for both moving and non-moving improvement methods is characterized and compared to other systems that attempt to accomplish the same end using different means.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectSTAPen_US
dc.subjectMultistaticen_US
dc.subjectradaren_US
dc.subjectATRen_US
dc.subjectadaptive processingen_US
dc.subjectsignal processingen_US
dc.subjectdetectionen_US
thesis.degree.namePhDen_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineElectrical & Computer Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorGoodman, Nathanen_US
dc.contributor.advisorMelde, Kathleenen_US
dc.contributor.chairGoodman, Nathanen_US
dc.contributor.chairMelde, Kathleenen_US
dc.contributor.committeememberMarcellin, Michael W.en_US
dc.identifier.proquest2608en_US
dc.identifier.oclc659748533en_US
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