Synthetic Aperture Radar Imagery Is Constant False Target Detection

Target detection in Synthetic Aperture Radar (SAR) imagery plays very important role in Automatic Target Recognition (ATR). Constant False Alarm Rate (CFAR) processing of SAR images facilitates target detection in spatially varying background clutter. This dissertation focuses on the research of automatic target detection in SAR imagery using CFAR techniques, which are suitable for the characteristics of distributions of sea and ground clutter respectively.For target detection in sea clutter, especially ship detection, by choosing K, Log-normal, Weibull and Gamma distributions as model for the clutter distribution, the mathematic expression of adaptive threshold is calculated, and the automatic target detection algorithm is accomplished.The background clutter environment is more complex in ground target detection than in ship detection. By using Rayleigh, Log-normal, Weibull, Pearson distributions, which are suitable for the characteristics of ground clutter, and cell average (CA), greatest of (GO), order statistics (OS) CFAR methods, the software of ground target detection algorithm is developed. Comparison and analysis are made among the performance of each CFAR method in various background clutters.