Title :
Approximate eigenvalue distribution of a cylindrically isotropic noise sample covariance matrix
Author :
Tuladhar, Saurav R. ; Buck, John R. ; Wage, Kathleen E.
Author_Institution :
ECE Dept., Univ. of Massachusetts, North Dartmouth, MA, USA
Abstract :
The statistical behavior of the eigenvalues of the sample covariance matrix (SCM) plays a key role in determining the performance of adaptive beamformers (ABF) in presence of noise. This paper presents a method to compute the approximate eigenvalue density function (EDF) for the SCM of a cylindrically isotropic noise field when only a finite number of shapshots are available. The EDF of the ensemble covariance matrix (ECM) is modeled as an atomic density with many fewer atoms than the SCM size. The model results in substantial computational savings over more direct methods of computing the EDF. The approximate EDF obtained from this method agrees closely with histograms of eigenvalues obtained from simulation.
Keywords :
approximation theory; array signal processing; covariance matrices; density functional theory; eigenvalues and eigenfunctions; statistical distributions; adaptive beamformers; approximate eigenvalue distribution; atomic density; cylindrically isotropic noise; eigenvalue density function; ensemble covariance matrix; Atomic measurements; Computational modeling; Covariance matrix; Eigenvalues and eigenfunctions; Electronic countermeasures; Noise; Polynomials; Cylindrically Isotropic Noise; Polynomial Method; Random Matrix Theory; Sample Covariance Matrix;
Conference_Titel :
Statistical Signal Processing Workshop (SSP), 2012 IEEE
Conference_Location :
Ann Arbor, MI
Print_ISBN :
978-1-4673-0182-4
Electronic_ISBN :
pending
DOI :
10.1109/SSP.2012.6319833
