Single-Channel Blind Signal Separation Method for Time-frequency Overlapped Signal Based on CEEMD-FastICA

This paper presents a new methodology for single-channel blind signal separation (SCBSS) of time-frequency overlapped signals in electromagnetic surveillance domain. This method combines the complete ensemble empirical mode decomposition (CEEMD) with fast independent component analysis (FastICA). Firstly, the single-channel recording is decomposed into a set of intrinsic mode function (IMF) components by the method CEEMD with adaptive noise, for the residue and the number of shifting iterations of CEEMD are smaller than that of other empirical mode decomposition approach. The IMF components become the basis representing the original data. After selecting the usefull IMF components according to their power spectrum, FastICA is used to separate the source of interest in the original signal. Simulation results obtained in evaluating the proposed methodology's performance confirmed the feasibility and effectiveness of this algorithm.