Eigenspace-based linearly constrained minimum variance beamformer

The eigenspace-based linearly constrained minimum variance beamformer (ELCMVB) is presented in this paper, which combines the linearly constrained minimum variance beamformer (LCMVB) with the eigenspace-based beamformer. The ELCMVB projects the presumed steering vector of the LCMVB onto the signal subspace, the projected steering vector is then used to calculate the weight, vector for beamforming with the linearly constrained minimum variance technique. Compared to the generalized eigenspace-based beamformer(GEIB), the ELCMVB removes the computation of the modified signal subspace. So it can avoid the numerical instability. The theoretical analysis also indicates that the ELCMVB is not affected by the positions of the null constraints in performance. Computer simulation results are presented and demonstrate the merits of the ELCMVB.