Accelerating Distributed Synthetic Aperture Radar Data Simulations Via CUDA

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dc.contributor.advisorPan, Chongle
dc.contributor.authorRackelin, Eric
dc.contributor.committeeMemberGoodman, Nathan
dc.contributor.committeeMemberKong, Martin
dc.date.accessioned2022-05-06T15:14:00Z
dc.date.available2022-05-06T15:14:00Z
dc.date.issued2022-05
dc.date.manuscript2022-05
dc.description.abstractA general simulation of distributed synthetic aperture radar (DSAR) data is useful to evaluate the theoretical performance of a DSAR system and its underlying algorithms without a deployed system in place. Simulating DSAR is a computationally intensive task due to the size and complexity of the resultant data, but a simulation must complete within a reasonable amount of time to be a useful tool in practice. Through the use of both MATLAB and CUDA, a DSAR simulation can be flexible and modifiable while benefiting from efficiently implemented GPU acceleration. Multiple simulation programs have been developed using these programming languages to explore techniques of parallelizing and optimizing the performance of DSAR data simulation.en_US
dc.identifier.urihttps://hdl.handle.net/11244/335563
dc.languageen_USen_US
dc.subjectRadaren_US
dc.subjectGPUen_US
dc.subjectHigh Performance Computingen_US
dc.thesis.degreeMaster of Scienceen_US
dc.titleAccelerating Distributed Synthetic Aperture Radar Data Simulations Via CUDAen_US
ou.groupGallogly College of Engineering::School of Computer Scienceen_US

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