Processing Of Microwave Interferometry Data For Plume Plasma Density Diagnosis

Microwave interferometer is an efficient tool for non-intrusively diagnosis of electron number density of plasma, which can be used for the measurement of plume.In this thesis, several diagnostics for electron density are compared. The theory and design of microwave interferometry for plasma diagnostics are briefly introduced. Four different numerical Abel inversion algorithms for the retrieval of plume density profile by microwave interferometry, including the discretization method, the cubic spline interpolation method, the Hankel-Fourier transform method and the Nestor-Olsen method, are compared for the cases with and without noise. After analysis of the effect of sampling density on the retrieval performances, the smoothing and interpolating solution is proposed to mitigate the under-sampling related problem. The procedures of the retrieval and processing are proposed.Two experiments, using a microwave network analyzer for accurate differential phase measurement are described. In the first experiment, a pipe is measured as the simulated target, and the retrieval results match well with the shape of the pipe. In the second experiment, spatial resolved integrated phase shifts are retrieved by Abel algorithm. The radial electron density profile within the plume of helicon plasma thruster is calculated. The experiments and their results verified the performance and validity of both the system design and the retrieval algorithm.Based on the experiment, it is proved that the algorithms proposed in this thesis are robust and easily implemented, which is important for the implementation of the systems for future applications.