WL distribution modeling of X-band small grazing Angle sea clutter via IPSO algorithm

In order to improve the heavy-tailed phenomenon in sea clutter modeling, the WL distribution modeling method and its statistical characteristics are studied. The IPSO (Improved Particle Swarm Optimization ) algorithm is used to estimate the sea clutter modeling parameters that obey the WL distribution, so as to improve the fitting effect of the statistical distribution model on sea clutter data. Based on the measured data of X-band sea clutter, the fitting effect of WL distribution on the measured data of sea clutter under different sea conditions is analyzed. Through the comparison with the goodness of fit test of statistical distribution models such as Rayleigh distribution, Weibull distribution, lognormal distribution and K distribution, it is shown that the WL distribution can well fit the sea clutter data with heavy tailing phenomenon, and has better statistical modeling ability of sea clutter amplitude distribution.