An efficient method for chaotic signal parameter estimation

Chaotic signals represent a new class of signals that can be applied in a wide range of signal processing applications. This paper describes an efficient method for parameter estimation of chaotic sequences generated by iterating tent maps with a known initial condition, and observed in white noise. The method is based on the connection between the symbolic sequence associated to the chaotic signal and the parameter of the tent map. The proposed method is asymptotically unbiased, and is found to attain the Cramer-Rao Lower Bound (CRLB) for a high Signal to Noise Ratio (SNR).