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dc.contributor.advisorStiles, James M.
dc.contributor.advisorBlunt, Shannon D.
dc.contributor.authorTan, Peng Seng
dc.date.accessioned2018-02-01T02:42:43Z
dc.date.available2018-02-01T02:42:43Z
dc.date.issued2017-05-31
dc.date.submitted2017
dc.identifier.otherhttp://dissertations.umi.com/ku:15282
dc.identifier.urihttp://hdl.handle.net/1808/25865
dc.description.abstractThis dissertation attempts to address a significant challenge that is encountered by the users of the Radio Frequency (RF) Spectrum in recent years. The challenge arises due to the need for greater RF spectrum by wireless communication industries such as mobile telephony, cable/satellite and wireless internet as a result of growing con-sumer base and demands. As such, it has led to the issue of spectrum congestion as radar systems have traditionally maintain the largest share of the RF spectrum. To resolve the spectrum congestion problem, it has become even necessary for users from both radar and communication systems to coexist within a finite spectrum allocation. However, this then leads to other problems such as the increased likelihood of mutual interference experienced by all systems that are coexisting within the finite spectrum.. In order to address this challenge, the dissertation will seek to resolve it via a two-step approach that are described as follows. For the first step of this approach, it will present a structured and meticulous approach to design a sparse spectrum allocation optimization scheme that will lead to the release of valuable spectrum previously allocated to radar applications for reallocation to other players such as the wireless video-on-demand and telecommunication industries while maintaining the range resolution performance of these radar applications. This sparse bandwidth allocation scheme is implemented using an optimization process utilizing the Marginal Fisher information (MFI) measure as the main metric for optimization. Although the MFI approach belongs to the class of greedy optimization methods that cannot guarantee global convergence, the results obtained indicated that this approach is able to produce a locally optimal solution. For the second step of this approach, it will present on the design of a spectral efficient waveform that can be used to ensure that the allocated spectrum limits will not be violated due to poor spectral emission containment. The design concept of this waveform is based on the joint implementation of the first and higher orders of the Poly-phase coded Frequency Modulated (PCFM) waveform that expands previous research on first order PCFM waveform. As any waveform generated using the PCFM framework possesses good spectral containment and is amenable to high power transmit operations such as radar due to its constant modulus property, thus the combined-orders of PCFM waveform is a very suitable candidate that can be used in conjunction with the sparse bandwidth allocation scheme in the first step for any radar application such that the waveform will further mitigate the issue of interference experienced by other users coexisting within the same band.
dc.format.extent202 pages
dc.language.isoen
dc.publisherUniversity of Kansas
dc.rightsCopyright held by the author.
dc.subjectElectrical engineering
dc.subjectIntegrated Sidelobe Level
dc.subjectIterative Minimum Mean Square Estimator
dc.subjectMarginal Fisher Information
dc.subjectPeak Sidelobe Level
dc.subjectPolyphase-coded Frequency Modulated
dc.subjectSparse Spectrum Allocation
dc.titleAddressing Spectrum Congestion by Spectrally-Cooperative Radar design
dc.typeDissertation
dc.contributor.cmtememberAllen, Christopher
dc.contributor.cmtememberLiu, Lingjia
dc.contributor.cmtememberDuncan, Tyrone
dc.thesis.degreeDisciplineElectrical Engineering & Computer Science
dc.thesis.degreeLevelPh.D.
dc.identifier.orcid
dc.rights.accessrightsopenAccess


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