Moving ordered statistics CFAR detection for nonhomogeneous backgrounds

A new robust order statistic-based CFAR scheme, the moving ordered statistics (MOS) CFAR detector, is proposed. The MOS-CFAR detector effectively estimates the noise level in nonhomogeneous backgrounds by using the spatial subspace concept and the order statistics estimation method. Like the OS-CFAR detector, the MOS-CFAR processor selects one of the reference cells as the estimate of the background noise power. However, the rank of the selected sample is a variable and varies depending on the different background noise distributions in the reference cells. The detection performances of the MOS-CFAR processor is investigated and compared with other well known CFAR detectors by means of simulations. The results show that the proposed MOS-CFAR detector is superior to the other schemes in regulating the false alarm rate in nonhomogeneous backgrounds