Blind estimation of the PN sequence and information sequence of a DSSS signal based on SVD

With focus on blind estimation of the Pseudo-Noise (PN) sequence of a Direct Sequence Spread Spectrum (DSSS) signal in non-cooperative spread spectrum communications, a blind estimation approach of PN sequence and information sequence is proposed based on Singular Value Decomposition (SVD). The chip rate of the PN sequence and the PN sequence period need to be known. Firstly, SVD is applied to the signal observation matrix made up of received signal. Then, the estimation of the PN sequence is obtained based on the left singular vector. At the same time, the information sequences can be estimated with the signal sequence unsynchronized and the PN sequence unknown through the right singular vector. Simulation experiment results verify that the proposed approach is of high stability, high accuracy, low computational complexity and short observation time.