ESTIMATION OF A SIGNAL WAVE-FORM FROM NOISY DATA USING LOW-RANK APPROXIMATION TO A DATA MATRIX

We present an analysis and improvement of a data-adaptive signal estim ation algorithm. Perturbation analysis of a reduced-rank data matrix i s used to reveal its statistical properties. The obtained information is used for calculating the performance of the Toeplitz-restoration al gorithm of Tufts, Kumaresan, and Kirsteins. This analysis leads to imp rovements of the method, and the predicted improvements are demonstrat ed by simulation and comparison with the Cramer-Rao bounds.