• DocumentCode
    1766408
  • Title

    New Spatial Correlation Models for Sea Clutter

  • Author

    Hao Ding ; Jian Guan ; Ningbo Liu ; Guoqing Wang

  • Author_Institution
    Dept. of Electron. & Inf. Eng., Naval Aeronaut. & Astronaut. Univ., Yantai, China
  • Volume
    12
  • Issue
    9
  • fYear
    2015
  • fDate
    Sept. 2015
  • Firstpage
    1833
  • Lastpage
    1837
  • Abstract
    In this letter, new models for the spatial correlation of sea clutter texture and intensity are proposed as improved versions of current power law models or exponential decay model. The models for texture have three unknown parameters, and thus can be called triparametric models. The structure of the models is a weighted sum of two components, which can describe the decaying process of the correlation coefficient with spatial lags, as well as the periodic behavior due to the existence of transient coherent structures in sea clutter. Unknown parameters are optimized by the nonlinear least square fit method. Models for sea clutter intensity can be obtained through a linear transform for uncorrelated speckle based on the compound-Gaussian representation of sea clutter. The proposed models are validated and compared with current models using S- and C-band measured sea clutter data. Analysis results indicate the effectiveness of the proposed models in that they can describe the behavior of spatial correlation coefficients with higher accuracy.
  • Keywords
    oceanographic techniques; C-band measured sea clutter data model; S-band measured sea clutter data model; correlation coefficient decaying process; exponential decay model; linear transform; nonlinear least square fit method; power law model; sea clutter intensity model; sea clutter intensity spatial correlation; sea clutter spatial correlation model; sea clutter texture spatial correlation; sea clutter transient coherent structure; spatial correlation coefficient behavior; texture model; triparametric model; uncorrelated speckle based compound-Gaussian representation; weighted component sum model structure; Clutter; Correlation; Data models; Radar clutter; Sea measurements; Speckle; Compound-Gaussian model; sea clutter; spatial correlation property; texture; triparametric models;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2015.2430371
  • Filename
    7126972