MEAN-LEVEL DETECTION IN THE FREQUENCY-DOMAIN

Conventional mean-level detection (cell-averaging CFAR) is applied to frequency-domain data obtained by using the discrete Fourier transform (DFT) as a bank of Doppler filters. It is shown that the scalloping t hat results from use of the DFT not only results in a loss in SNR, but also causes a limiting, or compression, of the detection probability. This compression is due to the contamination of the mean-level estima te by the presence of significant signal components in all filters, wh ich occurs when the Doppler frequency is not exactly the centre of a D oppler filter. Applying a window (e.g. Hamming) to the data does not a lleviate the compression problem. However, it is shown that zero paddi ng the data, which is the conventional approach to avoiding scalloping loss, also prevents compression of the detection probability when a t echnique called odd-even processing (OEP) is used. Results given show that using zero padding and OEP leads to only a small loss compared wi th optimum mean-level detection applied in the case when the Doppler f requency is assumed known.