• DocumentCode
    3212718
  • Title

    Applying hidden Markov models to radar detection in clutter

  • Author

    Stein, D.W.J. ; Dillard, G.M.

  • Author_Institution
    NCCOSC RDTE, USA
  • fYear
    1997
  • fDate
    14-16 Oct 1997
  • Firstpage
    586
  • Lastpage
    590
  • Abstract
    Sea clutter amplitude is often modeled as a compound random variable Z=AX, where A is a positive valued random variable and X has a Rayleigh distribution. The K and discrete Rayleigh mixture distributions arise from this model using a gamma or discrete distribution, respectively, for A. In certain applications, successive values of A may be correlated. If this correlation is modeled as a finite Markov process, Z is described by a hidden Markov model (HMM). Amplitude only and phase coherent detection statistics are derived from the HMM models using locally optimal and likelihood ratio techniques, respectively. The performance of these algorithms are compared with CFAR and Doppler processors using radar data
  • Keywords
    radar clutter; CFAR; Doppler processors; HMM; K distribution; Rayleigh distribution; algorithms; amplitude detection statistics; compound random variable; correlation; discrete Rayleigh mixture distribution; discrete distribution; finite Markov process; gamma distribution; hidden Markov models; likelihood ratio techniques; locally optimal techniques; performance; phase coherent detection statistics; positive valued random variable; radar data; radar detection; sea clutter amplitude;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Radar 97 (Conf. Publ. No. 449)
  • Conference_Location
    Edinburgh
  • ISSN
    0537-9989
  • Print_ISBN
    0-85296-698-9
  • Type

    conf

  • DOI
    10.1049/cp:19971742
  • Filename
    629246