The effects of signal contamination on two adaptive detectors

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 _D and false alarm performance (ghosting probability P _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 _D and P _G are computed as a function of the false alarm probability P _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 _D and P _G decrease with increasing levels of contamination. The P _G performance is is almost identical for the GLRT and MLAD. The P _D performance shows similar relative performance trends. Significantly, it is shown that the ghosting probability does not exceed P _F in the presence of contamination.<>