• DocumentCode
    1295318
  • Title

    Statistical scattering model for high-resolution sonar images: characterisation and parameter estimation

  • Author

    Bisceglie, M.D. ; Galdi, C. ; Griffiths, H.D.

  • Author_Institution
    Facolta di Ingegneria, Univ. degli Studi del Sannio, Benevento, Italy
  • Volume
    146
  • Issue
    5
  • fYear
    1999
  • fDate
    10/1/1999 12:00:00 AM
  • Firstpage
    264
  • Lastpage
    272
  • Abstract
    The statistical mechanism ruling the reverberation from the seabed in high-resolution sonar devices is investigated. The signal received from a sonar cell is assumed to arise from the coherent sum of a random number of independent elementary contributions. Under proper conditions regarding the surface roughness and the incidence angle, the observables can be modelled as compound-Gaussian random variables with a nonuniform distribution of phase. A general expression has been found for evaluating the first- and second-order probability density function of the complex observables, and the case corresponding to a gamma distributed texture is investigated. The authors also propose a technique for estimating parameters of the generalised K distribution based on approximating the design distribution with a neighbouring family. Results have demonstrated that the algorithm achieves good performance within the examined range of parameter values
  • Keywords
    acoustic wave scattering; gamma distribution; image resolution; image texture; parameter estimation; probability; reverberation; rough surfaces; sonar imaging; statistical analysis; complex observables; compound-Gaussian random variables; first-order probability density function; gamma distributed texture; generalised K distribution; high-resolution sonar images; incidence angle; nonuniform phase distribution; parameter estimation; reverberation; seabed; second-order probability density function; statistical scattering model; surface roughness;
  • fLanguage
    English
  • Journal_Title
    Radar, Sonar and Navigation, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-2395
  • Type

    jour

  • DOI
    10.1049/ip-rsn:19990711
  • Filename
    819793