Low complexity robust beamformer for general-rank signal model based on uniform linear array

Based on the uniform linear array (ULA) structure and the resultant persymmetric structure of its covariance matrices, a low complexity robust beamformer for an incoherently general-rank signal model is proposed by introducing a preprocessing transformation matrix. The computational complexity is reduced significantly due to a real-valued close-form solution for the optimum weight vector. Moreover, the proposed algorithm can achieve a higher output signal-to-interference-plus-noise ratio (SINR).