Statistical signal processing in broadband reflectometry

Abstract

Microwave broadband reflectometry is used to determine the spatial distribution of plasma density (density profile) in experimental nuclear fusion devices. The position of each plasma reflecting layer is evaluated by Abel integration of the phase rate of the reflectometric signal that results from mixing the plasma incident and reflected waves. The signal processing problem is cast in the stochastic nonlinear filtering framework. The phase/frequency corresponding to the reflecting layer dynamics is modeled as a two-dimensional Markovian process, from which only one component (phase) is observed. Guided by these (noisy) observations a suboptimal filter propagates the joint (phase/frequency) a posteriori probability density function, allowing to estimate the phase rate. The purpose is to develop a robust and versatile tool to process reflectometric data. >