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A new CFAR detector based on ordered statistics and cell averaging

This paper presents a new CFAR detector based on ordered statistics and cell averaging, as well as the automatic censoring technique. It is known as "mean of order statistics and cell averaging" (MOSCA) processor. For this new CFAR detector we obtain analytic expressions of the false alarm rate, the detection probabilities and measure average decision threshold (ADT) under the Swerling II assumption. Its detection performance is analyzed in homogeneous background and in the presence of strong interfering targets, and we compare it with CA and OS CFARs. The analysis shows that performance of the MOSCA-CFAR detector is between the CA and OS CFAR processor in homogeneous background. In multiple target situations the MOSCA-CFAR detector is much better than the OS-CFAR detector.