Eigenspace-Based Linearly Constrained Minimum Variance Beamformer
基于特征空间的线性约束最小方差波束形成器

By combining the Linearly Constrained Minimum Variance Beamformer(LCMVB) with the eigenspace-based beamformer, this paper presents the Eigenspace-based Linearly Constrained Minimum Variance Beamformer(ELCMVB). The ELCMVB first projects the presumed steering vector of the LCMVB onto the signal subspace, then gets the weight vector by using the LCMV and the projected steering vector. The theoretical analysis indicates that the ELCMVB outperforms the Generalized Eigenspace-based Beamformer(GEIB).Compared to the GEIB, the ELCMVB removes the computation of the modified signal subspace and overcomes the numerical instability. Null constraints hardly affect the performance of the ELCMVB. Computer simulation results are also presented and demonstrate the merits of the ELCMVB.