Spectrum sensing is the key function of Cognitive Radios which act as secondary users and dynamically access vacant frequency bands. In practice, this sensing function is fulfilled by detecting the existence of primary users' signals. Almost all modulated signals show cyclostationarity characteristics which are suitable for signal detection. Some specific signals (e.g. Interleaved Frequency Division Multiple Access (IFDMA) signal) regularly distributed in frequency domain possess specific cyclostationarity distribution feature which can be utilized to construct a signal detector. In this paper, cyclostationarity feature matched detection (Abbr. is the cyclostationarity detection during the following parts) based on the correlation of signal inherent distribution in frequency domain is proposed. We give the theoretical deduction of the proposed method and an application example built on the practical IFDMA signal. The proposed detection scheme is simple and efficient because only parts of frequency bands are examined. Simulation results show that the detection performance of the proposed scheme precedes that of the conventional energy detection and so called suboptimum cyclostationarity detection which is built without known signal distribution information. This paper gives the insight that signal inherent distribution information and signal (Cyclic Periodogram) CP distribution information are useful for the design of simple and efficient spectrum sensors.