Detection of random signals by integrated polyspectral analysis

We consider the problem of detecting an unknown, random, stationary signal (Gaussian or non-Gaussian) in Gaussian noise of known correlation structure. No other assumptions are made about the signal to be detected. We suggest two approaches utilizing both the power spectrum and the third- and fourth-order integrated polyspectra for the detection of random signals. The detector structures of the proposed approaches are derived, and their performance is evaluated via simulations and comparisons with the classical energy detector involving both Gaussian and non-Gaussian signals. It is shown that the power of one of the proposed tests is competitive with that of the energy detector for Gaussian signals, and it outperforms the energy detector for the non-Gaussian signals tested.