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dc.contributor.advisorAbd-Alhameed, Raed
dc.contributor.advisorJones, Steven M.R.
dc.contributor.advisorNoras, James M.
dc.contributor.authorAl-Sadoon, Mohammed A.G.
dc.date.accessioned2022-02-15T16:05:27Z
dc.date.available2022-02-15T16:05:27Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/10454/18747
dc.description.abstractThis thesis is concentrated on the Angle / Direction of Arrival (A/DOA) estimation and Beamforming techniques that can be used in the current and future engineering applications such as tracking of targets, wireless mobile communications, radar systems, etc. This thesis firstly investigates different types of AOA and beamforming techniques. A comprehensive comparison between the common AOA algorithms is performed to evaluate the estimation accuracy and illustrate the computational complexity of each algorithm. The effect of mutual coupling between the radiators and the impact of the position-error of the antenna elements on the estimation accuracy is also studied. Then, several new efficient AOA methods for current wireless localisation systems are proposed. The estimation accuracy and computational complexity are compared with well-known AOA methods over a wide range of scenarios. New methodologies for Covariance Matrix (CM) sampling are proposed to enhance and improve operational performance without increasing the computational burden. A new beamforming algorithm is proposed and implemented on a compact mm-Wave linear and planar antenna arrays to enhance the desired signal and suppress the interference sources in wireless communication systems. The issue of asset tracking in dense environments where the performance of the Global Positioning System (GPS) becomes unavailable or unreliable is addressed in the thesis as well. The proposed solution uses a low-profile array of sensors mounted on a finite conducting ground. A compact-size omnidirectional spiral sensor array of six electrically small dual-band antenna elements was designed to operate in the 402 and 837 MHz spectrum bands. For the lower band, a three-element superposition method is applied to support the estimated AOA whereas six sensors are considered for the higher band. An efficient and low complexity Projection Vector (PV) AOA method is proposed. An Orthogonal Frequency Division Multiplexing (OFDM) modulation is integrated with the PV technique to enhance the estimation resolution. The system was found to be suitable for installation on top of vehicles to localise the position of assets. The proposed system was tested to track non-stationary objectives, and then two scenarios were investigated: outdoor to outdoor and outdoor to indoor environments using Wireless In-Site Software. The results confirm that the proposed tracking system works efficiently with a single snapshot.en_US
dc.description.sponsorshipHigher Commission for Education Development (HCED) in Iraq Basra Oil Company Ministry of Oilen_US
dc.language.isoenen_US
dc.rights<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.en_US
dc.subjectDirection/Angle of Arrival (DOA/AOA)en_US
dc.subjectAntenna arrayen_US
dc.subjectAdaptive beamformingen_US
dc.subjectSignal processingen_US
dc.subjectOutdoor-Indoor localisationen_US
dc.subjectTracking systemsen_US
dc.subjectMutual couplingen_US
dc.subjectMultiple Input Multiple Output (MIMO)en_US
dc.subjectWireless mobile communicationsen_US
dc.subjectOrthogonal Frequency Division Multiplexing (OFDM)en_US
dc.subjectNarrow and wideband spectrumsen_US
dc.titleDirection Finding and Beamforming Techniques using Antenna Array for Wireless System Applicationsen_US
dc.type.qualificationleveldoctoralen_US
dc.publisher.institutionUniversity of Bradfordeng
dc.publisher.departmentFaculty of Engineering and Informaticsen_US
dc.typeThesiseng
dc.type.qualificationnamePhDen_US
dc.date.awarded2019
refterms.dateFOA2022-02-15T16:05:27Z


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