Abstract
AbstractAlpha stable distribution is better for modelling impulsive noises than Gaussian distribution in signal processing. This class of process has no close form of probability density function and finite second order moments. This paper addresses the direction of arrival estimation and beamforming problems of mobile communication system with linear antenna arrays in high impulsive noise environment. In order to reduce the computational complexity, the problems of DOA and beamforming are approached as a nonlinear mapping that can be modelled using a suitable radial‐basis function neural network (RBFNN). This paper also proposes the application of a three–layer RBFNN to perform the DOA estimation and beamforming in presence of alpha stable distribution noises. The performance of the network is compared to that of the fractional lower order statistics based algorithms. Simulations show that the RBFNN is appropriate to approach the DOA estimation and beamforming. At the same time, the RBFNN substantially reduces the computation complexity. Copyright © 2008 John Wiley & Sons, Ltd.
Published Version
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