Fast algorithm for direction-of-arrival estimation based on cyclic propagator method

A fast cyclic-SSF (signal subspace fitting) algorithm for direction-of-arrival (DOA) estimation in array processing referred to as cyclic propagator method (CPM) is proposed in this paper. Compared with the conventional eigen subspace algorithms, the presented method has lower computational complexity with insignificant performance degradation because of avoiding the SVD (singular value decomposition) of the data matrix or EVD (eigen value decomposition) of the covariance matrix of the received signals. Furthermore, by exploiting cyclostationarity, the new algorithm is a signal-selective DF algorithm. The signal-selectivity eliminates the need for knowledge of the characteristics of the noise or interference in the environment, and, enables the new algorithm to resolve a number of desired signals not exceeding the number of sensors in the presence of arbitrary noise and a virtually unlimited number of unknown interferers. Computer simulations verified its effectivity.