Deconvolution-Based Retrieving of Plasma Electron Temperature Pedestal from Thomson Scattering JET Core LIDAR Data
We demonstrate the resolving of the electron temperature pedestal from the Thomson scattering Core LIDAR data in the JET tokamak. The proposed novel method is based on the deconvolution of Core LIDAR profiles and the use of a specific fitting algorithm applied to the deconvolved and convolved (by a defined low-pass filter) estimates of electron temperature profiles of variable pedestal parameters. We present this method in preparation of the expected upgrade of the core LIDAR system in terms detector sensitivity and higher sampling rate of the digitisers. The method application to the current JET Core LIDAR data requires over-sampling of original LIDAR profiles (3cm step) to a new sampling scale of 1cm step. Then we apply an optimal three-parameter least-square algorithm to extract the best fit of the electron temperature pedestal parameters (amplitude, width and position) at a given pedestal shape. As a result, we retrieve the electron temperature profile over the entire plasma diameter with a step of 1cm, including the resolved pedestal. The simulation analysis by a computer model, based on the TS Core LIDAR parameters, demonstrates the expected performance of the full processing algorithm based on the novel method.