A robust minimum variance distortionless response algorithm and its application

Generally, the adaptive beamformer has better spatial resolution and much better interference rejection capability than the conventional data-independent beamformer. But in practice, the performance of the traditional adaptive beamformer will degrade greatly if some assumptions or information on the propagation model, array parameters and signal model are imprecise. Therefore, it is very important to make the adaptive beamforming techniques less sensitive to the model mismatch and parameter uncertainties. In this paper, we propose a robust minimum variance distortionless response (R-MVDR) algorithm based on the worst-case performance optimization changing the constraint of MVDR. The analytic expression for the optimized weight vector is presented. The performance of R-MVDR is verified via the numerical and experimental results. It can be demonstrated that the arithmetic proposed has better spatial resolution and much better interference rejection capability with experimental data.