Novel Direction-Adaptive Based Reduced-Rank Beamforming Algorithm

Inhalt:
A reduced-rank method called joint iterative optimization direction-adaptive (JIO-DA) scheme is proposed for adaptive beamforming in large array scenarios based on the linear constraint minimum variance (LCMV) criterion. The proposed scheme jointly optimizes a reduced-rank filter and a transforming matrix. The columns of the transforming matrix are considered as direction vectors and are updated one by one. The recursive least-squares (RLS) algorithm is then developed to update these direction vectors and the reduced-rank filter. Simulation results show that the proposed scheme improves the convergence rate of beamforming with low computational complexity.