Blind robust neural network beamformer

Many blind beamforming algorithms, such as C-CAB, use the signal characteristics to estimate the steering vector. The conventional LCMV algorithm is then adapted to obtain the optimum solution. However, the LCMV-like methods are sensitive to the mismatch. In this paper, the cause of this mismatch is discussed in detail. A robust blind beamforming algorithm is presented. Using a neural network structure the algorithm can decrease the computational complexity and make it possible to realize the method in real time. Results of computer simulations are included to support our analysis