Performance analysis of Krylov space adaptive beamformers

The performance of Krylov subspace-based dimensionality reduction for adaptive beamforming is analyzed using a simple second-order Taylor series approximation to the mean output signal-to-noise ratio (SNR). It is shown that the predicted SNRs accurately follow the experimentally measured SNR and explain the threshold effects when the angles or spacing are varied between the signal mode (subspace) and interference modes (subspace). Furthermore, we discuss how the SNR approximation can be applied to calculating the deflection of a Krylov subspace dimension-reduced Capon´s test statistic.