Research Of Blind Source Separation On The Moving Platform

Blind source separation is a new type of technology,which is developed in the past two decades. BSS has made considerable development in theory and practical application,there are wide range of applications in various subject areas and many popular research directions. Many scholars are committed to the corresponding the field of theoretical and applied research, also they have achieved good results. In order to obtain valuable information in communication reconnaissance by array antenna equipment on board, blind source separation problem for the moving platform is mainly studied in this paper.An array to receive communication signals mixed model is established, the study found that the communication signal mixed model is equivalent to a time-varying linear instantaneous model,when the antenna array is moving. The classical blind source separation algorithm - the natural gradient algorithm and the EASI algorithm have been studied ,and then put forward several improved algorithms, make some simulation analysis. For the contradiction between convergence speed and steady-state performance in BSS, a new algorithm is proposed - kurtosis variable step-size EASI algorithm based on optimially selected function for blind source separation. According to the relationgship between the covariance of kurtosis and the state of separation ,the algorithm's step-size is controlled with kurtosis covariance, it decreases the steady-state error efficiently.Meanwhile optimially selected function algorithm carrys on two different estimation functions, which are used between two phases of the signal separation, as the result of the convergence speed has increased. The proposed algorithm has faster convergence speed and smaller steady-state error than EASI and VS_EASI. It applies to the time-varying linear instantaneous mixed model and separates mixed communication signals successfully.The new algorithm has extensive application prospects.