Asymptotic performance analysis of DOA finding algorithms with temporally correlated narrowband signals

This correspondence focuses on the asymptotic performance analysis of gener al direction-of-arrival (DOA) finding algorithms under the stochastic model assumption in which source and noise signals are possibly non-Gaussian and possibly temporally correlated, We prove, in particular, that all the cova riance-based DOA estimators are sensitive to the temporal correlation Of th e sources when the noise is temporally correlated; otherwise, most of them are insensitive to the temporal correlation of the sources except for the T oeplitzation and the augmentation techniques.