  In this work, we propose a low-complexity robust adaptive beamforming (RAB)
technique which estimates the steering vector using a Low-Complexity
Shrinkage-Based Mismatch Estimation (LOCSME) algorithm. The proposed LOCSME
algorithm estimates the covariance matrix of the input data and the
interference-plus-noise covariance (INC) matrix by using the Oracle
Approximating Shrinkage (OAS) method. LOCSME only requires prior knowledge of
the angular sector in which the actual steering vector is located and the
antenna array geometry. LOCSME does not require a costly optimization algorithm
and does not need to know extra information from the interferers, which avoids
direction finding for all interferers. Simulations show that LOCSME outperforms
previously reported RAB algorithms and has a performance very close to the
optimum.
