Systolic robust adaptive beamforming with an adjustable constraint

This paper presents a novel, fully parallel algorithm for robust linearly constrained minimum variance (LCMV) beamforming. The robustness results from the use of an adjustable constraint to compensate for the unavoidable small mismatch between the nominal and the actual steering vector of the signal-of-interest. The need for parallelism follows from the large computational demands of beamforming algorithms and by the high data rates which are typically present in communications applications. The algorithm exhibits good numerical properties as it is based on orthogonal transformations only. Two systolic architectures are presented on which the throughput is independent of the size of the beamformer