Scharf, Louis L., authorVan Veen, Barry, authorIEEE, publisher2007-01-032007-01-031990Van Veen, Barry D. and Louis L. Scharf, Estimation of Structured Covariance Matrices and Multiple Window Spectrum Analysis, IEEE Transactions on Acoustics, Speech and Signal Processing 38, no. 8 (August 1990): 1467-1472.http://hdl.handle.net/10217/738An intimate relationship between low rank modeling and multiple window spectrum estimation is demonstrated by using maximum likelihood estimates of structured covariance matrices. The power in a narrow spectral band is estimated by estimating the variances in a low rank signal plus noise covariance model. This model is swept through the entire frequency band to obtain an estimate of power as a function of frequency. The resulting spectrum estimates are given by weighted combinations of eigenspectra. Each eigenspectrum results from projecting the data onto an orthogonal component of the signal subspace and squaring. The multiple window spectrum estimates of Thomson correspond to a particular choice for the low rank signal model. The low rank modeling and structured covariance matrix framework is also used to derive the maximum likelihood estimate for the center frequency of a signal in noise. This estimate is also obtained from a weighted combination of eigenspectra.born digitalarticleseng©1990 IEEE.Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.spectral analysismatrix algebraestimation theoryText