Title :
An iterative subspace estimation method for adaptive array processing
Author :
Carhoun, Dean O.
Author_Institution :
The MITRE Corp., Bedford, MA, USA
Abstract :
The author presents a novel, low-complexity, iterative method of vector subspace estimation applicable to adaptive beamforming and spatial spectral estimation. This method combines two complementary procedures: the power/deflation method of principal eigenvector estimation and the Lanczos method of tridiagonalization for computing the orthonormal basis of a Krylov subspace. Side information concerning the spatial coherence of the deflated array data is developed to aid discrimination between the (coherent) signal and (noncoherent) noise subspaces. The effectiveness of the proposed method is demonstrated by processing a typical example of underwater acoustic receiver data based on N.L. Owsley´s (1991) Standard Test Case. The algorithm´s performance is compared with a baseline method that uses full singular value decomposition of the data
Keywords :
eigenvalues and eigenfunctions; iterative methods; parameter estimation; signal processing; Krylov subspace; Lanczos method; adaptive array processing; adaptive beamforming; baseline method; deflated array data; iterative subspace estimation; noise subspaces; orthonormal basis; power/deflation method; principal eigenvector estimation; side information; singular value decomposition; spatial coherence; spatial spectral estimation; tridiagonalization; underwater acoustic receiver data; vector subspace estimation; Acoustic beams; Acoustic noise; Acoustic testing; Array signal processing; Covariance matrix; Eigenvalues and eigenfunctions; Iterative methods; Singular value decomposition; Spatial coherence; Underwater acoustics;
Conference_Titel :
Signals, Systems and Computers, 1991. 1991 Conference Record of the Twenty-Fifth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-2470-1
DOI :
10.1109/ACSSC.1991.186597
