Abstract: We derive an estimator of the covariance matrix in
signal processing in the presence of white noise based on the method of maximum
likelihood estimation. The estimator is a continuous function of the eigenvalues
and eigenvectors of the matrix where is the sample covariance matrix of
observations consisting of both noise and signals. Strong consistency and
asymptotic normality of the estimator are discussed.
Keywords and phrases: maximum likelihood estimator, signal processing, white noise, colored noise.
