Beamformer design exploiting blind source extraction techniques

Recently we have shown how a blind source extraction (BSE) algorithm can be equipped with some prior information about mixing parameters of the desired source in order to extract this source. The prior information, which may contain errors, is used to construct a matrix from linear combinations of correlation matrices. The extraction filter is easily obtained from the specific eigenstructure of this matrix. Here we project the beamformer design problem onto the above mentioned BSE algorithm by parameterizing the mixing system. We show in three ways that the proposed method is efficient and flexible. First, with one procedure an LCMV and MVDR beamformer can be obtained. Second, by taking only two appropriate linear combinations of correlation matrices, which may be interpreted as selection beamformers, the desired source can be selected. Third, selection beamformers can be designed for a subset of sensors while the final beamformer exploits data from all sensors.