A New Blind Source Separation Algorithm Based on Second-Order Statistics for TITO

In this paper, we investigate a new blind source separation algorithm for TITO (two-input and two-output) channel system. Considering the case of the noisy instantaneous linear mixture of source signals, we form the matrix pair with the two 2×2 dimension symmetric, positive definite matrices via two covariance matrices. We apply a set of transforms such as the Cholesky factorization and SVD (singular value decomposition) to this formed matrix pair. And a unitary matrix is then obtained, which is an accurate diagonalizer of each matrix of this pair. Compared with the JADE algorithm and the SOBI algorithm, some numerical results show the better performance of the new algorithm.