New blind beamforming algorithm using joint multiple matrix diagonalization

We propose a new joint multiple matrix diagonalization algorithm for robust blind beamforming. This new algorithm is based on the iterative eigen-decomposition of cumulant matrices. Therefore it can avoid the stability and misadjustment problems arising among the conventional steepest-descent approaches for constant-modulus or cumulant optimization. Our Monte Carlo simulations show that our proposed algorithm significantly outperforms the JADE algorithm based on the Givens rotation for PSK source signals in terms of signal-to-interference-and-noise ratio for a wide variety of signal-to-noise ratios