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dc.contributor.advisorNamuduri, Kameswaraen_US
dc.contributor.authorKambhampati, Srisumakanth
dc.date.accessioned2009-05-04T19:17:12Z
dc.date.available2009-05-04T19:17:12Z
dc.date.copyright2008
dc.date.issued2008-08
dc.identifier.otherd08010
dc.identifier.urihttp://hdl.handle.net/10057/2003
dc.descriptionThesis (Ph.D.)--Wichita State University, College of Engineering Dept. of Electrical and Computer Engineeringen
dc.descriptionIncludes bibliographic references (leaves 69-76)en
dc.description.abstractParticle filtering techniques have captured the attention of many researchers in various communities, including those in signal processing, communication and image processing. Particle filtering is particularly useful in dealing with nonlinear state space models and non-Gaussian probability density functions. The underlying principle of the methodology is the approximation of relevant distributions with random measures composed of particles (samples from the space of the unknowns) and their associated weights. This dissertation makes three main contributions in the field of particle filtering. The first problem deals with target tracking in radar signal processing. The second problem deals with object tracking in video. The third problem deals with estimating error bounds for particle filtering based symbol estimation in communication systems.en
dc.format.extent1815431 bytes
dc.format.extentxi, 78 p.en
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen
dc.publisherWichita State Universityen
dc.rightsCopyright 2008 by Srisumakanth Kambhampati. All Rights Reserveden
dc.subject.lcshElectronic dissertationsen
dc.titleTarget/Object tracking using particle filteringen
dc.typeDissertationen


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  • CE Theses and Dissertations
    Doctoral and Master's theses authored by the College of Engineering graduate students
  • Dissertations
    This collection includes Ph.D. dissertations completed at the Wichita State University Graduate School (Fall 2005 --)
  • EECS Theses and Dissertations
    Collection of Master's theses and Ph.D. dissertations completed at the Dept. of Electrical Engineering and Computer Science

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