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In this thesis, an adaptive waveform selection technique for dynamic target tracking under low signal-to-noise ratio (SNR) conditions is investigated. The approach is integrated with a track-before-detect (TBD) algorithm and

In this thesis, an adaptive waveform selection technique for dynamic target tracking under low signal-to-noise ratio (SNR) conditions is investigated. The approach is integrated with a track-before-detect (TBD) algorithm and uses delay-Doppler matched filter (MF) outputs as raw measurements without setting any threshold for extracting delay-Doppler estimates. The particle filter (PF) Bayesian sequential estimation approach is used with the TBD algorithm (PF-TBD) to estimate the dynamic target state.

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    Date Created
    • 2011
    Resource Type
  • Text
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    Note
    • Partial requirement for: M.S., Arizona State University, 2011
      Note type
      thesis
    • Includes bibliographical references (p. 60-62)
      Note type
      bibliography
    • Field of study: Electrical engineering

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    by Ryan Piwowarski

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