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dc.contributor.advisorRedford, Gary
dc.contributor.authorDonovan, Nathan
dc.creatorDonovan, Nathan
dc.date.accessioned2019-06-13T03:49:29Z
dc.date.available2019-06-13T03:49:29Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/10150/632669
dc.descriptionGroup project with Sarah Rimsza, Mark Sackett, Logan Knott, Anthony Smith, and Nick Busker
dc.description.abstractThe paper Wide Area Drone Situational Awareness gives an in-depth walk through the Eyes in the Dark (EitD) drone detection system. The EitD system was designed to scan a portion of the sky for the presence of a drone. If the system detects a drone, EitD then uses its ability to alert a user to the detected object. Raytheon created the project to help secure small private airports from the ever-growing threat of small hobby drones. The EitD prototype satisfies all functional requirements except for the 400m distance requirement, which was not obtainable within the budget for the project. Both physical testing and theoretical analysis is presented to demonstrate the systems capabilities and areas of future work.
dc.language.isoen
dc.publisherThe University of Arizona.
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.
dc.titleWide Area Drone Situational Awareness
dc.typetext
dc.typeElectronic Thesis
thesis.degree.grantorUniversity of Arizona
thesis.degree.disciplineHonors College
thesis.degree.disciplineMechanical Engineering
thesis.degree.nameB.S.
refterms.dateFOA2019-06-13T03:49:29Z


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