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“Signal Detection in Incompletely Characterized Impulsive Noise using Lower--Order Statistics”
by George A. Tsihrintzis and Chrysostomos L. Nikias
March 1994
We address the problem of detection of signals of known shape but unknown strength in impulsive noise using lower--order statistics. We form a generalized likelihood ratio test which is based on moment, rather than maximum likelihood, estimates of the unknown parameters of the detection problem. We show that the moment estimates we propose are both asymptotically consistent and that the proposed generalized likelihood ratio test is asymptotically equivalent to the optimum likelihood ratio test corresponding to completely known signal and noise parameters (clairvoyant test). The proposed detection schemes can be very useful not only in the detection of sonar/radar/communication signals in impulsive interference, but also in other dual--use commercial applications.