Research On Separation Of Signal Components Of Multicomponent Signal

This dissertation focuses on the separation of overlapped signal components of the multicomponent signal which has various and important applications in the fields of communications, radar, sonar, speech, biomedical engineering and so on. Based on different analysis methods, various signal models are developed. Several theoretically and practically valued methods are proposed or derived to estimate the parameters of those models, and to perform the signal components separation. Computer simulations and their results are given to verify the efficiency of those proposed methods. The main contributions of this dissertation can be concluded as follows:(1) The definition, the separability, and existed separation approaches of the multicomponent signal are summarized. Based on this, the various separability analysis and separation approaches are carefully classified.(2) Based on the Weierstrass theory and PSP (Per-Survivor Processing), a model fitting based methods, which can separate the overlapped signal components of the multicomponent signal, is proposed. This method turns the problem of multi-signal components separation to that of the sequence and channel parameters estimation, which is much more convenient to process. Even in the situation that the spectra of the signal components are totally overlapped, they can be separated successfully by using this method.(3) A new method to separate the overlapped signal components of the multicomponent signal is proposed, which uses the short time and sinusoidal assumptions of the signal component, and extends the application of energy operator to the multi-signal components. The computational simplicity and high resolution properties of the energy operator are folly utilized, which leads to fast and accurate signal component separation.(4) Based on the idea of developing a time varying AR model for the multicomponent nonstationary signal, and using the time varying spectrum to estimate instantaneous frequency and amplitude for each signal component, a new...