A new Blind Source Separation algorithm based on non-orthogonal joint diagonalization of second-order statistics under lower SNR

To solve the problem of Blind Source Separation (BSS) of the communication signals without knowing the source number, we propose a new algorithm based on the second-order statistics. By jointly diagonalizing the time delay correlation matrix of the observed signals and using the improved new non-orthogonal joint diagonalization (NOJD), a better solution of BSS under lower SNR can be achieved. The simulation result shows that the proposed algorithm can successfully separate communication signals with SNR as low as 10dB under conditions such as the source number is unknown or dynamically changing, and in the over-determined mode regardless of the signals´ modulation methods. We use Signal to Interference Ratio (SIR), Crosstalk Error(CTE) and Correlation Coefficient as the performance indexes to prove the superiority of the proposed algorithm over the classical Second-Order Blind Identification (SOBI).