Performance Analysis of the FFT Filter Bank-Based Summation CFAR Detector

The constant false alarm rate (CFAR) detector based on the FFT filter bank is computationally efficient and widely used for the detection and frequency estimation of narrowband signals embedded in noise. The standard approach for improving its detection performance is to average the power spectral density (PSD) estimates obtained from multiple input data blocks prior to performing a detection decision. Since the variance of the averaged PSD estimates has an inverse linear dependence on the number of input data blocks, the conjecture that a 3 dB performance gain will result from doubling the number of input data blocks processed is plausible. However, this paper shows that the actual performance gain obtained with two input data blocks is less than 3 dB over the single block case and the performance gain for each successive doubling of the number of input data blocks decreases monotonically and appears to converge to a constant around 1.5 dB.