Intelligent CFAR detector for non-homogeneous weibull clutter environment based on skewness

In order to mitigate the performance degradation in non-homogeneous Weibull clutter environment, including multiple targets situation and clutter edge, a constant false alarm rate detector based on the skewness (SK) and mean ratio (MR) named SKMR-CFAR is proposed. In SKMR-CFAR, the reference window is divided into the leading and lagging windows, the skewness and mean ratio of the two windows are calculated respectively, and the clutter environment of reference window is determined by two hypothesis tests. Based on the test result, the appropriate window is selected to calculate the detection threshold. SKMR-CFAR exhibits a good detection performance in multiple targets situations and a robust false alarm control capacity at clutter edges. Simulation results verified the efficiency of proposed SKMR-CFAR detector.