A neural network approach of ultra-wideband nearfield adaptive beamforming

An adaptive beamforming method for ultrawide-band (UWB) array in the case of nearfield is proposed based on the radical basis function neural network (RBFNN) in this paper. The desired outputs corresponding with measured inputs for the nearfield impulse source are reflected into a set of training samples. Genetic algorithm and recursive least square algorithm are employed to determine the structure and the parameters of RBFNN. It can avoid the computation of an inverse matrix and alleviate the impact of the mutual coupling phenomenon. The experimental results also prove its efficiency and feasibility.