Modeling polarimetric SAR image based on Fisher distribution and its parameter estimation

Based on the Fisher multiple variable product model, the Fisher statistical model of polarimetric synthetic aperture radar(SAR) images is put forward to describe the properties of heavy tail and peak, and the statistics and the estimation methods are obtained. Firstly, the probability density function (PDF) of developed t distribution is given based on Cauchy distribution, so are the fractal moments. Secondly, the Fisher distribution model is obtained through the multiple variable product model mixed with the Fisher variable, and the PDF and the fractal moments of the covariance matrix moments are derived. At last, two estimation methods via Mellin transform and Matrix moments are presented. The performances of the novel data model and novel parameter estimation methods are verified by the simulated data and real data. The research provides a simple analytical method to describe different distributed clutter, which is useful to target detection and recognition.