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dc.contributor.authorKozy, Mark Alexanderen_US
dc.date.accessioned2019-06-13T08:00:24Z
dc.date.available2019-06-13T08:00:24Z
dc.date.issued2019-06-12
dc.identifier.othervt_gsexam:20201en_US
dc.identifier.urihttp://hdl.handle.net/10919/89948
dc.description.abstractIn this paper we address radar-communication coexistence by modelling the radar environment as a Markov Decision Process (MDP), and then apply Deep-Q Learning to optimize radar performance. The radar environment includes a single point target and a communications system that will potentially interfere with the radar. We demonstrate that the Deep-Q Network (DQN) we construct is able to successfully avoid interfering with the communication system to improve its performance. We also show that the DQN method outperforms previous methods in terms of memory and handling new situations. In this thesis we also address the application of the MDP into a software defined radio (SDR) USRP X310 by utilizing the software LabVIEW to communicate with and control the SDR.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis item is protected by copyright and/or related rights. Some uses of this item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectCognitive radaren_US
dc.subjectmachine learningen_US
dc.subjectreinforcement learningen_US
dc.subjecttracking radaren_US
dc.subjectsoftware defined radioen_US
dc.titleCreation of a Cognitive Radar with Machine Learning: Simulation and Implementationen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineElectrical Engineeringen_US
dc.contributor.committeechairBuehrer, Richard M.en_US
dc.contributor.committeememberReed, Jeffrey H.en_US
dc.contributor.committeememberRuohoniemi, John Michaelen_US


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