Particle Filtering for Noisy Contaminated Chaotic Signals and Its Application in Communications

The particle filter (PF) algorithm is proposed for realizing chaotic synchronization and communication in this paper. In our system, message symbols are modulated by additive and multiplicative chaos masking at the transmitter, and estimated by using the PF algorithm at the receiver. Simulation results indicate that the PF algorithm can effectively estimate the message symbols from the received signal. Compared with the unscented Kalman filter algorithm, the PF-based algorithm has a better performance in bit error rate (BER). In addition, BER of the additive chaos masking (ACM) scheme outperform that of the multiplicative chaos masking (MCM), which is close to that of BPSK at a higher E_b/N₀.