Neural networks-based DOA estimation of multiple stochastic narrow-band EM sources

Abstract

Localization of multiple stochastic narrow-band electromagnetic sources in the far-field is considered in the paper. Artificial neural networks-based approach is proposed to allow for an efficient direction of arrival (DOA) determination of electromagnetic signals radiated from stochastic sources as one of the key steps in the source localization procedure. It uses correlation matrix, obtained by signal sampling via antenna array in far-field scan area, to train an appropriate model based on MLP (Multi-Layer Perceptron) neural network. Proposed approach is validated on the example of a neural model performing accurate and fast one-dimensional (1D) DOA estimation of the position of three stochastic sources placed at fixed angle distance in azimuth plane.