A new beamforming algorithm based on signal subspace eigenvectors
Mehrzad Biguesh, Shahrokh Valaee, Benoı̂t Champagne, M. H. Bastani · 2002
A new beamforming algorithm, based on the eigendecomposition of the sample correlation matrix, has been introduced. The beamformer uses a weighted linear combination of the signal eigenvectors. Three versions of the beamformer have been proposed. It is shown that the proposed beamformer is a generalization of the delay-and-sum and the minimum variance beamformers. A linearly constrained minimum variance beamformer has also been derived. It is shown that the proposed approach induces robust beamformers.