An extended Cyclic MUSIC algorithm

Many modulated communication signals exhibit a cyclostationarity (or periodic correlation) property, corresponding to the underlying periodicity arising from carrier frequencies or baud rates. In this paper, we propose a new MUSIC-like direction-finding algorithm that exploits cyclostationarity in order to improve the direction-of-arrival (DOA) estimation. Both cyclic and conjugate cyclic correlation matrices are used in the proposed method so that it can be considered As an extension of the Cyclic MUSIC algorithm. The proposed cyclic method allows an increase in resolution power and noise robustness. Depending on the modulation type of incoming signals, the proposed method is also able to handle more sources than the number of sensors.