GENERALIZED EIGENSPACE-BASED BEAMFORMERS

The generalized eigenspace-based beam-former (GEIB) is presented here, which utilizes the eigenstructure of the correlation matrix to enhanc e the performance of the Linearly constrained minimum variance beamfor mer (LCMVB). The weight vector of the GEIB is found by projecting the LCMVB weight vector onto a vector subspace constructed from the eigens tructure of the correlation matrix, The GEIB and the LCMVB have the sa me responses to the desired signal and the interferers, However, the w eight vector of the GEIB has a smaller norm and generates a lower outp ut noise power. An additional advantage of the GEIB is that the linear constraints can be treated flexibly, i.e. each linear constraint can be chosen to be preserved or not preserved. The cost of preserving a l inear constraint is to get more output noise power, In addition to dev eloping the GEIB, we discuss the effects of imposing linear constraint s on the output noise powers of the GEIB and the LCMVB, Computer simul ations are also presented that demonstrate the merits of the GEIB.