Activity detection of communication signals is one of the most important tasks of unauthorized recievers. Detection is to derive the optimum receiver structure based on a criterion that is determined by the application. The Neyman-Pearson criterion is the well-known criterion for activity detection. Optimal (ideal) detectors require an essentially complete statistical description of the input signals and noise. In practice, this information may not be available a priori, and the statistics of the input data may also vary with time. These variations yield to change of false alarm probability of the detector. So, we need to employ some methods to keep the false alarm probability to be constant. In this situation, the detector is called a constant false alarm rate (CFAR) detector. In order to achieve CFAR property in varying environments, a basic approach is using an adaptive threshold. Heretofore so many detectors and algorithms have been introduced to reach CFAR property in radar applications but CFAR detectors have not been much considered for detection of communication signals specially spread spectrum signals. Therefore, the CFAR principles in radar systems should be tailored for detection of communication signals. Time-frequency cells are the subjects that have been introduced for this reason. In this research, we review the principles of detection in communication systems and survey some of the most important Frequency hopping signal is another spread spectrum signal that we review and survey some of its most important detectors. Among all kind of detectors, channelized radiometer is selected as the most important detector for detection of FH signals. The performance of a channelized radiometer is studied when different CFAR strategies are used to set the detection threshold. Since the channelized radiometer can be used in spectrum sensing in cognitive radio, we introduce cognitive radio systems and survey spectrum sensing methods. We propose a CFAR method for channelized radiometer which has a better performance comparing with other CFAR processors. Key Words: presence signal detection, Constant false alarm rate (CFAR), Linear frequency modulated (LFM), Frequency Hopping (FH), Channelized Radiometer
