The effects of signal contamination on two adaptive detectors

Abstract

Two schemes for adaptive detection Kelly's generalized likelihood ratio test (GLRT) and the mean level adaptive detector (MLAD), are analyzed with respect to the deleterious effect of desired-signal contamination of the data used to compute the sampled covariance matrix for the two detectors. The detection probability P/sub D/ and false alarm performance (ghosting probability P/sub G/) are predicted for the two schemes under the assumptions that the input noises are Gaussian random variables that are temporally independent but spatially correlated; and the amplitude of the desired signal is Rayleigh distributed. P/sub D/ and P/sub G/ are computed as a function of the false alarm probability P/sub F/ with no contamination, the number of input channels, the number of independent samples-per-channel, the matched filtered output signal-to-noise (S/N) power ratio, and the S/N power ratio of the contaminating desired signal. It is shown that both P/sub D/ and P/sub G/ decrease with increasing levels of contamination. The P/sub G/ performance is is almost identical for the GLRT and MLAD. The P/sub D/ performance shows similar relative performance trends. Significantly, it is shown that the ghosting probability does not exceed P/sub F/ in the presence of contamination. >