On Improvements of Cyclic MUSIC

Abstract

Many man-made signals encountered in communications exhibit cyclostationarity. By exploiting cyclostationarity, cyclic MUSIC has been shown to be able to separate signals with different cycle frequencies, thus, to be able to perform signal selective direction of-arrival (DOA) estimation. However, as will be shown in this paper, the DOA estimation of cyclic MUSIC is actually biased. We show in this paper that by properly choosing the frequency for evaluating the steering vector, the bias of DOA estimation can be substantially reduced and the performance can be improved. Furthermore, we propose another algorithm exploiting cyclic conjugate correlation to further improve the performance of DOA estimation. Simulation results show the effectiveness of both of our methods.