Research Of High-order Statistics Method Based On Blind Source Separation For Communication Signals

Modern, in the complicated communication environment, separating numerous mixed signals and acquire the needed signal becomes more and more important. The traditional signal separation method use the separation technique based on time-frequency. Without knowing the transcendental knowledge first about blind signals, it is very difficulty to separate communication signal of mixed frequency spectrum in the frequency area. As a new method in the signal processing, blind signal separation (BSS) beyond the limitation of signal processing technologies based on time-frequency. It can recover source signal from mixed signal without the prior information about source signal and the channel. Present, blind source separation has been applied to many fields such as communication, iatrology, image and array signal processing. It is an active-research area in signal processing.This paper introduced relevant concept and principle of blind signal separation in the first. Then, it carried on summary and elaboration for blind signal separation method based on instantaneous linear mix. This paper compared various method and in-depth research for blind signal separation method based on high-order statistics (HOS). BSS algorithms have been researched on two aspects, analyzed the feasibility which used it in separation of communication signal, and proposed improved algorithms, respectively. The simulation results show that the improved algorithms are effective and advantaged. On the base of above study, the thesis expanded communication signals to radar signals, and applies BSS method to the problem of radar signals separation. It obtained eximious results. So it provided a new method in separation problem of radar signals.