The application of improved covariance estimation to adaptive beamforming and detection

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