A novel worst-case robust beamformer based on interference-plus-noise covariance reconstruction and uncertainty level estimation

A variant of adaptive worst-case (WC) beamformer is devised in this paper, which is robust against arbitrary unknown signal steering vector (SSV) mismatches. Compared with the conventional WC beamforming approach, the proposed method is further improved in terms of robustness by reconstructing the interference-plus-noise covariance matrix (IN-CM) and adaptively adjusting the uncertainty level of the SSV errors. In particular, the INCM is obtained by using the Capon spatial spectrum as the power distribution, and then the uncertainty level is estimated by maximizing the output power. Simulation results are included to illustrate the superiority of the proposed method.