Overdetermined blind source separation: using more sensors than source signals in a noisy mixture

This paper addresses the blind source separation problem for the case where more sensors than source signals are available. A noisy-sensor model is assumed. The proposed algorithm com-prises two stages, where the first stage consists of a principal com-ponent analysis (PCA) and the second one of an independent com-ponent analysis (ICA). The purpose of the PCA stage is to increase the input SNR of the succeeding ICA stage and to reduce the sen-sor dimensionality. The ICA stage is used to separate the remain-ing mixture into its independent components. A simulation exam-ple demonstrates the performance of the algorithm proposed. 1