Adaptive Multiple-Beamformers for Reception of Coherent Signals with Known Directions

Two novel adaptive multiple-beamformers for reception of coherent signals with known directions-of-arrival (DOAs) in the presence of uncorrelated interferences are proposed. The first approach is a two-step solution as follows: estimate the amplitudes of all the coherent signals using a subspace method and then construct the linearly constrained minimum variance beamformer from the generalized array manifold. The second approach applies multiple linear constraints determined from the DOAs of the coherent signals to develop a minimum variance beamformer, which can achieve efficient signal utilization. To cope with performance degradation due to sample covariance errors, DOA estimation errors and other array imperfections, the eigenstructure of the covariance matrix is exploited to improve the performance of the proposed approaches by constraining the weight vector in the signal subspace. Simulation results are presented which compare the performance of the proposed algorithms with that of the minimum mean square error approach.