Title :
Minimum variance linear estimation of amplitudes for exponential signal models
fDate :
9/1/1999 12:00:00 AM
Abstract :
This article presents the minimum variance consistent linear estimator for amplitude parameters in exponential signal models. A simple heuristic algorithm is presented to compute the weighting matrix that minimizes error variance; the resulting weighted least squares estimator accounts for the statistics of pole estimation errors. Additionally, analysis of binary diagonal weighting matrices demonstrates that for unweighted least-squares, the amplitude variance is reduced by truncating the Vandermonde system of equations
Keywords :
amplitude estimation; error analysis; least squares approximations; matrix algebra; signal processing; Vandermonde equations truncation; amplitude estimation; amplitude parameters; amplitude variance; binary diagonal weighting matrices; error statistics; error variance minimisation; exponential signal models; heuristic algorithm; minimum variance linear estimation; pole estimation errors; unweighted least-squares; weighted least squares estimator; weighting matrix; Additive noise; Amplitude estimation; Analysis of variance; Damping; Equations; Error analysis; Frequency estimation; Heuristic algorithms; Least squares approximation; Maximum likelihood estimation;
Journal_Title :
Signal Processing, IEEE Transactions on