Title :
Eigendecomposition methods for frequency estimation: a unified approach
Author :
Banjanin, Z. ; Cruz, J. ; Zrnic´, D.S.
Author_Institution :
Oklahoma Univ., Norman, OK, USA
Abstract :
A unified approach to three eigendecomposition-based methods for frequency estimation in the presence of noise is presented. These are the Tufts-Kumaresan (TK) method, the minimum-norm (MN) method, and the total-least-squares (TLS) method. It is shown that the MN method is a modified version of the TK method and the TLS method is a generalization of the MN methods. The TLS solution vector is expressed in matrix form, and an alternate way of computing it is presented. The MN methods exhibit some improvement over the TK method
Keywords :
eigenvalues and eigenfunctions; estimation theory; least squares approximations; noise; spectral analysis; MN method; TK method; TLS method; Tufts-Kumaresan; eigendecomposition-based methods; frequency estimation; matrix form; minimum-norm; noise; solution vector; total-least-squares; Computer science; Equations; Frequency estimation; Gaussian noise; Least squares approximation; Least squares methods; Matrix decomposition; Maximum likelihood estimation; Meteorology; Storms;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on
Conference_Location :
Albuquerque, NM
DOI :
10.1109/ICASSP.1990.116143
