Robust adaptive beamforming using sequential quadratic programming

In this paper, a new algorithm for robust adaptive beamforming is developed. The basic idea of the proposed algorithm is to estimate the difference between the actual and presumed steering vectors and to use this difference to correct the erroneous presumed steering vector. The estimation process is performed iteratively where a quadratic convex optimization problem is solved at each iteration. Unlike other robust beamforming techniques, our algorithm does not assume that the norm of the mismatch vector is upper bounded, and hence it does not suffer from the negative effects of over/under estimation of the upper bound. Simulation results show the effectiveness of the proposed algorithm.