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dc.contributor.authorVelmurugan, Rajbabuen_US
dc.date.accessioned2007-05-25T17:40:00Z
dc.date.available2007-05-25T17:40:00Z
dc.date.issued2007-04-03en_US
dc.identifier.urihttp://hdl.handle.net/1853/14611
dc.description.abstractThis thesis contributes new algorithms and implementations for particle filter-based target tracking. From an algorithmic perspective, modifications that improve a batch-based acoustic direction-of-arrival (DOA), multi-target, particle filter tracker are presented. The main improvements are reduced execution time and increased robustness to target maneuvers. The key feature of the batch-based tracker is an image template-matching approach that handles data association and clutter in measurements. The particle filter tracker is compared to an extended Kalman filter~(EKF) and a Laplacian filter and is shown to perform better for maneuvering targets. Using an approach similar to the acoustic tracker, a radar range-only tracker is also developed. This includes developing the state update and observation models, and proving observability for a batch of range measurements. From an implementation perspective, this thesis provides new low-power and real-time implementations for particle filters. First, to achieve a very low-power implementation, two mixed-mode implementation strategies that use analog and digital components are developed. The mixed-mode implementations use analog, multiple-input translinear element (MITE) networks to realize nonlinear functions. The power dissipated in the mixed-mode implementation of a particle filter-based, bearings-only tracker is compared to a digital implementation that uses the CORDIC algorithm to realize the nonlinear functions. The mixed-mode method that uses predominantly analog components is shown to provide a factor of twenty improvement in power savings compared to a digital implementation. Next, real-time implementation strategies for the batch-based acoustic DOA tracker are developed. The characteristics of the digital implementation of the tracker are quantified using digital signal processor (DSP) and field-programmable gate array (FPGA) implementations. The FPGA implementation uses a soft-core or hard-core processor to implement the Newton search in the particle proposal stage. A MITE implementation of the nonlinear DOA update function in the tracker is also presented.en_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectSequential Monte Carlo methoden_US
dc.subjectBayesian estimationen_US
dc.subjectConfigurableen_US
dc.subjectHardwareen_US
dc.subjectMixed-signalen_US
dc.subjectAnalog signal processingen_US
dc.subjectRange onlyen_US
dc.subjectBearings onlyen_US
dc.subjectComplexityen_US
dc.subjectArchitectureen_US
dc.subject.lcshTracking radar Mathematicsen_US
dc.subject.lcshTarget acquisitionen_US
dc.subject.lcshSound-waves Measurementen_US
dc.subject.lcshKalman filteringen_US
dc.titleImplementation Strategies for Particle Filter based Target Trackingen_US
dc.typeDissertationen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.description.advisorCommittee Chair: McClellan, James; Committee Member: Anderson, David; Committee Member: Davis, Jeffrey; Committee Member: Lanterman, Aaron; Committee Member: Vidakovic, Branien_US


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