Nonparametric estimation of the cyclic cross spectrum

Cyclostationary processes are an important class of nonstationary processes. We consider nonparametric estimation of the cyclic cross spectrum. A smoothed periodogram-based estimator is studied and its asymptotic behavior characterized, extending univariate work to the multivariate case. Application to cyclic coherence measurements is discussed. The results are useful in a variety of multisensor cyclostationary signal processing scenarios such as time delay and bearing estimation.