Skip to Main Content
The purpose of the work presented here is to determine which signal model, stationary or cyclostationary, is more suitable for signal detection in different representative cases. We consider different detectors depending on the available signal knowledge. As cyclostationarity-based detectors, the multi-cycle, single-cycle, and a new detector for unknown signals, denoted maximum spectral correlation amplitude (MSCA) detector, are analyzed. The MSCA detector performs an efficient search on the whole cyclic spectrum based on the fast Fourier transform (FFT) accumulation method (FAM) for cyclic-correlation estimation. Analytical approximations of the false alarm and detection probabilities of the MSCA detector are derived. Additionally, the optimum radiometer and a channelized radiometer are included in the work as radiometric detectors. All these detectors are designed for stationary white Gaussian noise (WGN), their sensitivity is evaluated also for different nonideal environments, which comprise nonstationary or non-Gaussian noise. Our results show that, in general, cyclostationarity-based detectors only find application when the noise power is unknown and it is not possible to use a CFAR (constant false alarm rate) strategy for the radiometer.