We consider the problem of detecting a known signal with constant magnitude immersed in noise of unknown variance,

when the propagation channel is frequency-flat and randomly

time-varying within the observation window. A Basis Expansion

Model with random coefficients is used for the channel, and a Generalized Likelihood Ratio approach is adopted in order to cope with deterministic nuisance parameters. The resulting scheme can be seen as a generalization of the well-known

Matched Filter detector, to which it reduces for timeinvariant

channels. Closed-form analytical expressions are provided for the distribution of the test statistic under both hypotheses, which allow to assess the detection performance.

JF - IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2012)
PB - IEEE
CY - Kyoto, Japan
ER -