Performance Analysis of Multivariate Complex
Luzhou Xu, Jian Li · 2005
We consider multivariate complex amplitude es- timation in the presence of unknown interference and noise. Two multivariate approaches (Maximum Likelihood (ML) and Capon) are provided. We derive the closed-form expression of the Cramer-Rao bound (CRB) for the unknown complex amplitudes. We also analyze the bias properties and Mean Squared Errors (MSE) of the two estimators. A comparative study shows that the multivariate ML estimator is unbiased, whereas the multivariate Capon estimator is biased downward for finite snapshots. Both es- timators are asymptotically statistically efficient when the number of snapshots is large. Index Terms—Capon, complex wishart, Cramer-Rao bound, growth curve, ML, multivariate parameter estimation.