A Estimation of Signal-to-Interference-Plus-Noise Ratios (SINRs) Exploiting Non-stationarity

Abstract

Our discussion about optimum data-dependent beamforming has shown that the second-order statistics of the sensor signals w.r.t. the desired signal and w.r.t. interference-plus-noise are required for realizing robust optimum datadependent beamformers. For realizations in the DFT domain, especially, estimates of power spectral densities and of spatio-spectral correlation matrices w.r.t. the desired signal and w.r.t. interference-pl us-noise are necessary. Consider, e.g., the optimum MMSE beamformer in the DTFT domain after (4.110) that requires the PSD and the spatio-spectral c orrelation matrix of interference-plus-noise. Such estimates can be obtained with, e.g., the minimum statistics after [Mar01a] using the generalization of [Bit02] for estimating spatio-spectral correlation matrices w.r.t. interference-plus-noise. However, these methods assume a slowly time-varying PSD of i nterference-plus-noise relative to a strongly time-varying PSD of the desired signal.