Statistical Analysis of High Resolution TerraSAR-X Images for Ground Targets Detection

TerraSAR-X is a new generation of high-resolution (1 m) space borne Synthetic Aperture Radar (SAR) satellite, which makes ground targets detection (GTD), one of the hot problems in SAR image application fields, possible. As for the mostly used CFAR algorithm for GTD, the statistical analysis of SAR image is an essential step in threshold calculation. However, it has been proved that the traditionally used Rayleigh distribution is no longer suitable to modelling the statistical characteristics of 1 m resolution TerraSAR-X image with ground targets. To model these heavy-tailed distributions, some other distributions, including Gamma, Weibull, lognormal and K distribution models have been applied. According to the analysis of large numbers of experiment results, lognormal distribution model is selected to describe the statistical characteristics of the high resolution SAR images with ground targets. Then genetic algorithm (GA) is adopted to efficiently estimate the model parameters as accurately as possible, which are subsequently used to calculate the global CFAR detection threshold. The experiments indicate that, lognormal distribution model with GA based parameters computation are more suitable than Gamma, Weibull and K distribution models to describe the statistical characteristics of the high resolution SAR images, which is propitious to performance improvement of the global CFAR algorithm.