Study On Online Algorithm Of Blind Source Separation Based On Independent Component Analysis

Under the situation with unknown transmit channel and unknown sources, only the observation data received by the sensors can be used to resume the source signals, which is called the blind source separation (BSS). Because its wide application prospects in many fileds, such as aerial array signal processing, multiuser's communication, the speech and medical signal processing, thus it becomes the research focus in the signal processing recently. The algorithm of blind source separation includes offline batch processing and online selfadaptation processing. Under the situation of changeable channel or realtime processing necessary, the online selfadaptation algorithm must be adopted. However, there are two crucial problems for online algorithm: slow convergence speed and the fluctuation in steady state. Any research has been done of the online algorithm for blind source separation in this paper, exactly regards to improve the convergence speed and precision in steady state.This paper has explained the main solution of the blind source separation problem systematically at first :The independent component analysis (ICA) . From the signal model, the uncertainty and basic supposing of ICA was analyzed, the measurement criterion of independent degree and its consistency was studied. Some kinds of optimized algorithm and performance index of algorithm are summarized.By analysized the main factor which Influente the performance of online algorithm, combined the characteristic of the relevant algorithm itself, two differente variable step-size update rule based on natural gradient algorithm and extended Infomax algorithm respectively were proposed: (1) Two stage step-size update rule was proposed based on natural gradient algorithm. It divides the process of separation into two stages by using the independent measurement of the outputs. We adopt different variable step-size algorithm at different stage. It can detect whether the channel matrix is changed or not efficinently. So this algorithm can separate single distribute source efficinently under the situation for variable channel or invariable channel. (2)Based on extended Infomax algorithm, an improved online estimation model of the kurtosis was introduced, which is according to the detection of mixed channel matrix.Through analysing the relation between the kurtosis curve and separate state, proposed a novel step-size update rule based on the covariance of kurtosis. Compared with past algorithm, this algorithm not merely restrains the speed fast, the stable state error is little, and can be suitable for the environment that channel matrix change.Finally, more complicated over-complete BSS have been studied, analyzed the characteristic of every algorithm deeply, divided them into two kinds, introduced the main thought, advanced and disadvanced,the suitable environment of most algorithms, and has discussed the next research direction.