Performance degradation of DOA estimators due to unknown noise fields
F. Li, Richard J. Vaccaro · IEEE Transactions on Signal Processing · 1992
A statistical performance analysis of subspace-based directions-of-arrival (DOA) estimation algorithms in the presence of correlated observation noise with unknown covariance is presented. The analysis of five different estimation algorithms is unified by a single expression for the mean-squared DOA estimation error which is derived using a subspace perturbation expansion. The analysis assumes that only a finite amount of array data is available.>