On A Real-valued EVD Approach to Cyclic DOA Estimation

By exploiting the real-valued eigen decomposition (EVD) of the centro-Hermitian matrix, a novel cyclic MUSIC algorithm with signal selective property is presented by introducing a new forward backward smoothed covariance matrix. Compared with cyclic MUSIC algorithm, the proposed approach has a better performance in the presence of multipath propagation. In addition, this approach not only reduces the computational complexity, but also allows to select desired signals and to ignore interferences by exploiting the cyclostationarity property of signals of interest (SOIs). Simulation results that illustrate the performance of this approach in conjunction with cyclic MUSIC algorithm are described