Real-time algorithm for adaptive beamforming using cyclic signals

Adaptive beamforming using signal cyclostationarity can preserve the desired signal and cancel the interferers without prior information of the steering vector. We consider the Cross-SCORE processor which is one of this class of beamformers and uses time-consuming eigenvalue decomposition (EVD) to compute the weight vectors. Thus, this processor is not suitable for real-time processing. We apply a modular Gram-Schmidt orthogonalization (GSO) structure in conjunction with a power normalization scheme to the Cross-SCORE processor and propose a LMS based adaptive algorithm to update the weight vectors. Due to the pipeline and parallel properties of the modular GSO structure, our approach is very suitable for real-time processing and the required computing time for the array to process an output is O(N), where N is the number of array elements.