Abstract: Applying the particle filter (PF) technique, this paper proposes a PF-based algorithm to blindly demodulate the chaotic direct sequence spread spectrum (CDS-SS) signals under the colored or non-Gaussian noises condition. To implement this algorithm, the PFs are modified by (i) the colored or non-Gaussian noises are formulated by autoregressive moving average (ARMA) models, and then the parameters that model the noises are included in the state vector; (ii) the range-differentiating factor is imported into the intruder’s chaotic system equation. Since the range-differentiating factor is able to make the inevitable chaos fitting error advantageous based on the chaos fitting method, thus the CDS-SS signals can be demodulated according to the range of the estimated message. Simulations show that the proposed PF-based algorithm can obtain a good bit-error rate performance when extracting the original binary message from the CDS-SS signals without any knowledge of the transmitter’s chaotic map, or initial value, even when colored or non-Gaussian noises exist.
This is an open access article distributed under the
Creative Commons Attribution License which permits unrestricted use, distribution,
and reproduction in any medium, provided the original work is properly cited.
Export to BibTeX
MDPI and ACS Style
Li, T.; Zhao, D.; Huang, Z.; Liu, C.; Su, S.; Zhang, Y. Blind Demodulation of Chaotic Direct Sequence Spread Spectrum Signals Based on Particle Filters. Entropy 2013, 15, 3877-3891.
Li T, Zhao D, Huang Z, Liu C, Su S, Zhang Y. Blind Demodulation of Chaotic Direct Sequence Spread Spectrum Signals Based on Particle Filters. Entropy. 2013; 15(9):3877-3891.
Li, Ting; Zhao, Dexin; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhang, Yimeng. 2013. "Blind Demodulation of Chaotic Direct Sequence Spread Spectrum Signals Based on Particle Filters." Entropy 15, no. 9: 3877-3891.