Robust adaptive beamforming based on response vector optimization

In this paper, a robust beamforming method is proposed. This method can be viewed as a LCMV beamformer with its response vector further optimized. To generate a better response vector, it is first established as a non-convex quadratically constrained quadratic programming problem, and then is transformed into a semidefinite programming problem which can be efficiently and exactly solved via semidefinite relaxation. This method outperforms the traditional LCMV beamformer with lower sidelobe and well-maintained mainbeam. Moreover, the computation complexity is negligible because the size of the response vector is relatively small. Simulation examples are carried out to demonstrate the effectiveness of the proposed method.