Radar cross section fluctuation characteristics of typical stealth aircraft

Radar cross section (RCS) fluctuation characteristics are used to predict radar's detection performance and evaluate aircraft's scattering characteristic. Azimuth RCS statistics under different incident conditions for six typical stealth aircraft at eight different bands each with two kinds of polarizations are obtained utilizing high-frequency electromagnetic computation method. Three kinds of relatively new fluctuation models are used to fit those statistics and some universal conclusions are made by analyzing all the fitting patterns. The Chi-square model gives a better peak value estimation for the probability density distribution curve but doesn't fit very well after the curve peak; the log-normal model often gives a higher estimation for the peak value but fits well after the curve peak; the fitting error of Chi-square model decreases when the double-degrees of freedom increases (to about 1.1-1.5), which results from the increasing ratio (about 0.1-1.0) of the mean square to the variance of the statistics, and according to the Kolmogorov-Smirnov testing method, the error is about 0.15 to 0.25; the fitting error of log-normal model also decreases (to about 1.5-5.0) when the ratio of mean to median value of the statistics decreases. When the statistics unit is dB·m², the log-normal model and Legendre polynomials model always fit the data well more widely and the error is generally lower than 0.10.