A blind algorithm for estimating pseudo-noise sequence of DSSS signal in lower SNR conditions

Abstract

According to the demand of spread spectrum signal processing in lower SNR conditions, a novel blind estimation algorithm of the pseudo-noise (PN) sequence for the direct sequence spread spectrum (DSSS) signal is proposed based on the similarities among the DSSS signals and the eigenanalysis technique. At first, through segmentation processing and average cross-correlation calculation, the starting symbol of PN sequence is determined. Next, by utilizing the eigenanalysis technique PN sequence can be estimated accurately without any information of the DSSS signal. Simulation results show that compared with the existing algorithms under the same condition, the proposed algorithm not only overcomes the partial-encode problem, but also improves estimation performance by 2dB. Therefore, the proposed algorithm achieves an accurate estimation of PN sequence in lower SNR conditions.