Title :
Analysis of estimation of signal parameters by linear-prediction at high SNR using matrix approximation
Author :
Tufts, D.W. ; Vacarro, R.J. ; Kot, A.C.
Author_Institution :
Dept. of Electr. Eng., Rhode Island Univ., Kingston, RI, USA
Abstract :
A greatly simplified calculation of the accuracy of estimates of the parameters of exponential signals is introduced. The authors assume that the estimates are obtained by first estimating the coefficients of a prediction-error filter (PEF) that arises in signal modeling by linear prediction. A simplified approach based on matrix approximation is used to calculate the statistics of the errors in the estimated signal parameters at high SNR. This approach provides insights for design and tractable formulas even for the case of multicomponent signals and Hankel or Toeplitz data matrices. The analyses are verified by simulation examples that include single- and multiple-component signals consisting of damped or undamped complex exponential signals in noise
Keywords :
approximation theory; filtering and prediction theory; matrix algebra; signal processing; Hankel data matrix; Toeplitz data matrices; damped signals; error statistics; exponential signals; filter coefficients; high SNR; linear prediction; matrix approximation; multicomponent signals; prediction-error filter; signal modeling; signal parameters estimation; simulation; undamped signals; Analytical models; Direction of arrival estimation; Error analysis; Frequency estimation; Matrix decomposition; Parameter estimation; Prediction methods; Signal analysis; Signal to noise ratio; Vectors;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on
Conference_Location :
Glasgow
DOI :
10.1109/ICASSP.1989.266899