Subspace decomposition-based correlation matrix multiplication

The correlation matrix, which is widely used in eigenvalue decomposition (EVD) or singular value decomposition (SVD), usually can be denoted by R = E[y
i
y′
i
]. A novel method for constructing the correlation matrix R is proposed. The proposed algorithm can improve the resolving power of the signal eigenvalues and overcomes the shortcomings of the traditional subspace methods, which cannot be applied to low SNR. Then the proposed method is applied to the direct sequence spread spectrum (DSSS) signal's signature sequence estimation. The performance of the proposed algorithm is analyzed, and some illustrative simulation results are presented.