A SCBSS methodology for time-frequency overlapped signals using non-negative matrix factorisation

Abstract

ABSTRACTThis article presents a new methodology for single-channel blind signal separation (SCBSS) of time-frequency overlapped signals in electromagnetic surveillance domain. The proposed algorithm is based on non-negative matrix factorisation (NMF) through a dynamical embedding framework. This method is deterministic requiring no priori information of the original signals. Firstly, a series of delay vectors of the single-channel recording are selected to construct an appropriate dynamical embedding matrix. NMF algorithm is used to decompose the dynamical embedding matrix. Then, a convenient expansion basis of original sources can be obtained, which will be projected back to the original measurement space according to the dynamical embedding framework. The power density spectrum of the projected components and the independent nature of original signals are employed to extract the interested signals from measurement space. The feasibility and effectiveness of proposed algorithm are proved by computer simulation.