Signal selective localization of nonGaussian cyclostationary sources

Novel direction-finding algorithms that exploit the nonGaussian and cyclostationary nature of communication signals are explored. The proposed methods that are appropriate for uniform linear arrays employ cyclic higher order statistics of the array output and suppress additive Gaussian noise of unknown spectral content, even when the noise shares common cycle frequencies with the nonGaussian signals of interest. In addition, cyclic higher order statistics are tolerant to nonGaussian interferences with cycle frequencies other than those of the desired signals and allow one to consistently estimate the angles of arrival of signal sources (per cycle) whose number can be greater than the number of sensors