The presence of a signal is not always easy to detect, particularly if there is a large search space or in low signal to noise ratio environments. Some types of signals can be detected based on prior knowledge regarding their periodicity or similar. However other types of signals are not so easily characterised by their periodicity and instead may possess periodicity in terms of their correlation functions. This is sometimes referred to as cyclostationarity or being periodically correlated. Typical signals possessing cyclostationarity include modulated telecommunication type signals, signals originating from rotating machinery and others such as signals affected by seasonality or similar. A signal possessing cyclostationarity can be more easily detected in the presence of noise and the mathematical properties of cyclostationarity can be used as part of this detection process. Difficulties can arise when there are imperfections in the received signal that can occur due to e.g. jitter and frequency offsets. This work investigated various approaches to efficiently detect cyclostationary signals in the presence of these types of effects.