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Synthetic Aperture Radar Image Background Clutter Fitting Using SKS + MoM-Based Distribution

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  • Zhengwei Zhu
  • Jianjiang Zhou
  • Hongyu Chu

Abstract

distribution can accurately model various background clutters in the single-look and multilook synthetic aperture radar (SAR) images and is one of the most important statistic models in the field of SAR image clutter modeling. However, the parameter estimation of distribution is difficult, which greatly limits the application of the distribution. In order to solve the problem, a fast and accurate distribution parameter estimation method, which combines second-kind statistics (SKS) technique with Freitas’ method of moment (MoM), is proposed. First we deduce the first and second second-kind characteristic functions of distribution based on Mellin transform, and then the logarithm moments and the logarithm cumulants corresponding to the above-mentioned characteristic functions are derived; finally combined with Freitas’ method of moment, a simple iterative equation which is used for estimating the distribution parameters is obtained. Experimental results show that the proposed method has fast estimation speed and high fitting precision for various measured SAR image clutters with different resolutions and different number of looks.

Suggested Citation

  • Zhengwei Zhu & Jianjiang Zhou & Hongyu Chu, 2015. "Synthetic Aperture Radar Image Background Clutter Fitting Using SKS + MoM-Based Distribution," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-11, September.
    • Handle: RePEc:hin:jnlmpe:864019
    DOI: 10.1155/2015/864019
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