Title page for etd-0906109-030910


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URN etd-0906109-030910
Author Yu-Tsen Lin
Author's Email Address No Public.
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Department Electrical Engineering
Year 2008
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Improved Particle Filter for Target Tracking in Decentralized Data Fusion System
Date of Defense 2009-07-20
Page Count 91
Keyword
  • decentralized data fusion
  • target tracking
  • particle filter
  • Abstract In this thesis, we investigate a decentralized data fusion system with improved
    particle filters for target tracking. In many application areas, it becomes essential
    to use nonlinear and non-Gaussian elements to accurately model the underlying
    dynamics of a physical system. Particle filters have a great potential for solving
    highly nonlinear and non-Gaussian estimation problems, in which the traditional
    Kalman filter and extended Kalman filter may generally fail. To improve the tracking
    performance of particle filters, initialization of the particles is studied. We
    construct an initial state distribution by using least square estimation. In addition,
    to enhance the tracking capability of particle filters, representation of target velocity
    by another set of particles is considered. We include another layer of particle
    filter inside the original particle filter for updating the velocity. In our proposed
    architecture, we assume that each sensor node contain a particle filter and there
    is no fusion center in the sensor network. Approximated a posteriori distribution
    at the sensor is obtained by using the local particle filters with the Gaussian mixture
    model (GMM), so that more compact representations of the distribution for
    transmission can be obtained. To achieve information sharing and integration, the
    GMM-covariance intersection algorithm is used in formulating the decentralized fusion
    solutions. Simulation results are presented to illustrate that the performance
    of the improved particle filter is better than standard particle filter. In addition,
    simulation results of target tracking in the sensor system with three sensor nodes
    are given to show the effectiveness and superiority of the proposed architecture.
    Advisory Committee
  • Jiann-Der Lee - chair
  • Jieh-Chian Wu - co-chair
  • Shiunn-Jang Chern - co-chair
  • Chin-Der Wann - advisor
  • Files
  • etd-0906109-030910.pdf
  • indicate in-campus access in a year and off_campus not accessible
    Date of Submission 2009-09-06

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