Performance Analysis of CFAR Detection of Fluctuating Radar Targets in Nonideal Operating Environments

A constant false alarm rate in the presence of variable levels of noise is usually a requirement placed on any modern radar. The CA - and OS-CFAR detectors are the most widely used ones in the CFAR world. The cell-averaging (CA) is the optimu m CFA R detector in terms of detection probability in ho mogeneous background when the reference cells have identical, independent and exponentially distributed signals. The ordered-statistic (OS) is an alternative to the CA processor, which trades a small loss in detection performance, relative to the CA scheme, in ideal conditions for much less performance degradation in non-ideal background environments. To benefice the merits of these well-known schemes, two modified versions (MX- & MN-CFAR) have been recently suggested. This paper is devoted to the detection performance evaluation of these modified versions as well as a novel one (ML-CFA R). Exact formu las for their false alarm and detection performances are derived, in the absence as well as in the presence of spurious targets. The results of these performances obtained for Rayleigh clutter and Rayleigh target indicate that the MN-CFAR scheme performs nearly as good as OS detector in the presence of outlying targets and all the developed versions perform much better than that processor when the background environment is homogeneous. When compared to CA-CFAR, the modified schemes perform better in an ideal condition, and behave much better in the presence of interfering targets.