Title :
The application of improved covariance estimation to adaptive beamforming and detection
Author :
Abraham, Douglas A. ; Dey, Dipak K.
Author_Institution :
Naval Underwater Syst. Center, New London, CT, USA
fDate :
31 Oct-2 Nov 1994
Abstract :
Adaptive beamformers often rely on estimates of the interference covariance structure. When minimal data is used in estimating the unknown covariance matrix, performance may be improved by modifying the eigenvalues of the sample covariance matrix. The orthogonally invariant covariance estimators proposed by Dey and Srinivasan [1985] and a constant risk, minimax estimator are applied to adaptive beamforming by considering the signal-to-interference ratio (SIR) loss factor of Reed, Mallett, and Brennan [1974] where the average SIR loss is seen to decrease, and, to adaptive detection, by considering the adaptive detectors of Kelly [1986] and Robey et. al. [1992] where detection performance is seen to improve
Keywords :
adaptive signal detection; adaptive signal processing; array signal processing; covariance matrices; eigenvalues and eigenfunctions; interference (signal); losses; minimax techniques; parameter estimation; signal sampling; adaptive beamforming; detection; detection performance; eigenvalues; improved covariance estimation; interference covariance; loss factor; minimax estimator; orthogonally invariant covariance estimators; sample covariance matrix; signal-to-interference ratio; unknown covariance matrix; Adaptive signal detection; Array signal processing; Covariance matrix; Eigenvalues and eigenfunctions; Interference; Matrix decomposition; Maximum likelihood detection; Maximum likelihood estimation; Minimax techniques; Statistical distributions;
Conference_Titel :
Signals, Systems and Computers, 1994. 1994 Conference Record of the Twenty-Eighth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-6405-3
DOI :
10.1109/ACSSC.1994.471538
