Extended-Kalman-filter-based chaotic communication

Together with the optimal linearization technique, an extended-Kalman-filter-basedchaotic communication is first proposed in this paper. First,the optimal linearization technique is utilized to find theexact linear models of the chaotic system at operating statesof interest. Then, an extended Kalman filter (EKF) algorithmis used to estimate both the parameters and states where themessage is already embedded. By using the EKF together withthe optimal linear model, the message can be recovered wellat the receiver's end. Numerical examples and simulations aregiven to show the effectiveness of the proposed methodology.