Blind estimation of the PN sequence for weak DSSS signals in dynamic environments
This paper presents a method of singular value decomposition (SVD) plus digital phase lock loop (DPLL) to solve the difficult problem of blind pseudo-noise (PN) sequence estimation for low signal to noise ratios (SNR) direct sequence spread spectrum (DS) signals in dynamic environments. Of course, the method needs to know the parameters of DS signal, such as the period and code rate of PN sequence. Firstly, the received signal is sampled and divided into non-overlapping signal vectors according to a temporal window, which duration is two periods of PN sequence. Then an autocorrelation matrix is computed and accumulated by the signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of this autocorrelation matrix. Further more, a DPLL is used to deal with the estimated PN sequence with residual carrier in dynamic environments, it estimates and tracks the residual carrier, removes the residual carrier in the end. Theory analysis and computer simulation results show that this method can realize the PN sequence blind estimation from lower SNR input DS signals in dynamic environments effectively.