Frequency spectrum estimation by autoregressive modeling

Abstract eng:
The paper deals with methods for frequency spectrum estimation by autoregressive modeling. Estimate of the autoregressive model parameters is the first step in this way of spectral analysis. The method used to do it are based on solving the system of normal equations, resulting from the least square method, or on solving the Yule-Walker equation and on Burg’s method. The least square method uses the Gram-Schmidt ortogonalisation and its modification. The YuleWalker equations are solved using Cholesky’s factorization and Levinson’s iterative method. The AR model parameters determine the transfer function of a linear system with white noise as an input signal. The frequency transfer function and the model error variance determine the frequency spectrum.

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