DIRECTION-OF-ARRIVAL ESTIMATION VIA EXPLOITATION OF CYCLOSTATIONARITY - A COMBINATION OF TEMPORAL AND SPATIAL PROCESSING

Many modulated communication signals exhibit a cyclostationarity (or periodic correlation) property, corresponding to the underlying periodicity arising from carrier frequencies or baud rates. By exploiting cyclostationarity, i.e., evaluating the cyclic correlations of the received data at certain cycle frequencies, we can extract the cyclic correlations of only signals with the same cycle frequency and null out the cyclic correlations of stationary additive noise and all other co-channel interferences with different cycle frequencies. Thus, the signal detection capability can be significantly improved. Cyclic correlation was first used into array signal processing by Gardner et al. However, their approach was based on a narrow-band data model, which is only exact for perfect narrow-band sinusoids; hence, their algorithms are approximate for general cyclostationary sources. In this paper, we propose a new approach for exploiting cyclostationarity that is asymptotically exact for either narrow-band or broad-band sources. Moreover, the new method also has significant implementational advantages over the earlier techniques. The simulation results indicate a significantly better performance for the new method in some environments.