A feasibility study for electromagnetic pollution monitoring by electromagnetic-source localization via neural independent component analysis

The aim of this paper is to present an electromagnetic source localization technique based on independent component analysis (ICA), as a part of a feasibility study for electromagnetic pollution monitoring via neural network techniques. Four ICA algorithms known from the literature, allowing to process complex-valued signals, are used to estimate the propagation parameters of electromagnetic fields emitted by radio-base transmission systems. By properly interpreting the results given by the ICA algorithms it is possible to develop a blind source localization procedure. The experiments are performed on synthetic signals generated according to realworld emission features, and are used to obtain a preliminary evaluation of the expected behavior of the localization system in a real-world context.