A modified eigen-structure analyzer to lower SNR DS-SS signals under narrow band interferences

This paper proposes a modified approach to eigen-structure analysis of direct sequence spread spectrum (DS-SS) signals under narrow-band interferences (NBIs), which can estimate the pseudo noise (PN) sequence blindly in lower signal-to-noise ratio (SNR) and signal-to-interference ratio (SIR) DS-SS signals. Of course, some parameters of DS-SS signals (such as the period and chip interval of PN sequences) need to be known. The received signal is divided into continuous non-overlapping temporal vectors according to two periods (not the one period before in [T. Zhang, A. Mu, C. Zhang, Analyze the eigen-structure of DS-SS signals under narrow band interferences, Digital Signal Process. 16 (6) (2006) 746–753]) of PN sequence, after which their correlation matrix is calculated and accumulated vector by vector. An eigenvalue decomposition operation can be applied to the matrices to analyze blindly the eigen-structure (including the NBI eigen-structures and PN sequences) of received signals from the principal component eigenvectors. Since the duration of temporal window is two periods of PN sequence, the PN sequence can be reconstructed by one principal eigenvector (not the two component eigenvectors before in [T. Zhang, A. Mu, C. Zhang, Analyze the eigen-structure of DS-SS signals under narrow band interferences, Digital Signal Process. 16 (6) (2006) 746–753]) only. Theoretic analysis and experimental results show that the approach is more effective than the method before in [T. Zhang, A. Mu, C. Zhang, Analyze the eigen-structure of DS-SS signals under narrow band interferences, Digital Signal Process. 16 (6) (2006) 746–753]. It can also work well in the lower SNR and SIR environments.