Title :
Shrinkage-Based Capon and APES for Spectral Estimation
Author :
Yang, Jun ; Ma, Xiaochuan ; Hou, Chaohuan ; Liu, Yicong
Author_Institution :
Inst. of Acoust., Chinese Acad. of Sci., Beijing, China
Abstract :
In this letter, we propose shrinkage-based Capon (S-Capon) and APES (S-APES) spectral estimators by minimizing the mean-square error (MSE) of standard Capon and APES in a linear regression framework. The proposed methods are shown to give more accurate spectral estimates but lower resolution than the methods they based on. We combine Capon with the proposed S-Capon and S-APES to overcome the resolution limit of shrinkage-based methods for estimation of both frequency and amplitude of spectral lines. The so-obtained Capon-SCapon and Capon-SAPES spectral estimators, which have about the same computational complexity as Capon, are compared with the Capon-APES (CAPES) by numerical examples. Simulations show that the Capon-SCapon performs similarly to CAPES in a wide range of signal-to-noise ratio, and the Capon-SAPES always gives more accurate spectral amplitude (less bias and lower MSE) than CAPES.
Keywords :
adaptive filters; adaptive signal processing; amplitude estimation; channel bank filters; computational complexity; frequency estimation; mean square error methods; minimisation; phase estimation; regression analysis; signal resolution; spectral analysis; MSE method; adaptive filterbank framework; amplitude-and-phase estimation; computational complexity; frequency estimation; linear regression framework; mean-square error minimization; shrinkage-based Capon-APES estimation; signal resolution; signal-to-noise ratio; spectral estimation; Amplitude and phase estimation; Capon spectral estimator; shrinkage estimates; spectral estimation;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2009.2026203