Abstract:

Chaotic DS signal is a kind of spread spectrum signal generated by directly modulating information signal with a chaotic signal. Communications using chaotic DS signals instead of conventional direct sequence spread spectrum signals have many advantages such as larger capacity and low probability of intercept. However, detection of chaotic DS signals is difficult. We propose a method to detect chaotic DS signals by calculating the largest Lyapunov exponent of the time series after being separated from the received signals using an ICA blind signals separation algorithm. Simulation results show feasibility of this method under Gaussian noise and multi-path channel interferences.

Key words: chaotic DS, signal detection, Lyapunov exponent, blind signals separation, independent component analysis