Estimation of Time-Varying Autoregressive Symmetric Alpha Stable

Especially the linear symmetric alpha-stable processes have found applications in various fields. When the process parameters are time- invariant, various techniques are available for estimation.

However, time-invariance is an important restriction given that in many communications applications channels are time-varying. For such processes, we propose a relatively new technique, based on particle filters which obtained great success in tracking applications involving non-Gaussian signals and nonlinear systems. Since particle filtering is a sequential method, it enables us to track the time-varying autoregression coefficients of the alpha-stable processes.