Neural network approach for efficient DOA determination of multiple stochastic EM sources in far-field

An efficient approach for determination of incoming direction of electromagnetic (EM) signals radiated from multiple stochastic sources in far-field is presented in this paper. The approach is based on using a neural model realized by the Multi-Layer Perceptron (MLP) artificial neural network. MLP neural model, successfully trained by using correlation matrix of signals sampled by receiving antenna array, can be used to accurately determine a direction of arrival (DOA) of radiated EM signals and afterward a location of each of multiple stochastic sources in azimuth plane. Presented model is suitable for real-time applications as it performs fast the DOA estimation. The model architecture, results of its training and testing as well as simulation results are described in details in the paper.