A new least squares approach to blind beamforming

We present a new two-step approach to blind beamforming based on the least squares criterion. The first step consists of "whitening" the array received vector, i.e., transforming its response matrix to some unknown unitary matrix. The second step consists of estimating the unitary matrix from the fourth order cumulants by a least squares criterion. In contrast to the corresponding "joint diagonalization" step of the JADE algorithm, our second step exploits all the structural information in the problem and consequently yields better performance. Simulation results demonstrating the improved performance over the JADE algorithm are included.