A novel algorithm for adaptive beamforming based on projection transformation

Abstract

An improved projection transformation method for enhancing the performance of the linearly constrained minimum variance beamformer is presented. The novel algorithm uses a projection operator, which is the basis vectors for the estimated signal-plus-interference subspace obtained by searching for it in the array manifold space by means of priori knowledge. The new algorithm can further reduce the computational complexity and eliminate the signal cancellation when a desired signal is contained in the correlation matrix. Moreover, the new method has a good beam pattern with lower sidelobe level and faster convergence speed in the case that there exist amplitude and phase errors and/or colored noise. The advantages are confirmed by computer simulations.