Novel efficient blind beamforming algorithm using cumulant optimization

Blind beamformers have drawn a lot of attention from signal processing researchers in the past decade. These new beamforming techniques based on the signal statistics can remove the restriction on minimum-variance distortionless beamformers, such as the narrow bandwidth of source signals, the spectral distinction between the source signal and interference, etc. We propose a novel efficient blind beamforming algorithm based on the optimization of cumulants. Instead of the existing slow-converging steepest-descent-search algorithm, we derive a new iterative method to achieve the optimal solution. Empirically speaking, our new algorithm requires only a few iterations to reach a satisfactory result. Monte Carlo simulations also show that our iterative blind beamforming algorithm is robust over different signal-to-noise ratio conditions.