Fast QRD-lattice-based unconstrained optimal filtering for acoustic noise reduction

We derive a fast QRD-least-squares lattice (QRD-LSL) based unconstrained optimal filtering algorithm for multi-channel acoustic noise reduction. As known from the literature, the unconstrained optimal filtering approach is an alternative to the popular GSC beamforming, which does not rely on a priori information and hence possesses improved robustness. The optimal filtering problem involved is special in that the desired response signal is not known explicitly. The derivation of the QRD-LSL algorithm is based on a significantly reorganized version of a QRD-RLS-based unconstrained optimal filtering scheme. Overall an order of magnitude complexity reduction is obtained without any performance penalty, which makes this new approach affordable for real time implementation.