Blind deconvolution extraction of Doppler-broadened spectra in LIF spectroscopy under model-free constraints

In plasma physics research, laser-induced fluorescence (LIF) spectroscopy is a crucial diagnostic tool for determining plasma parameters. To retrieve particle parameter distributions utilizing Doppler shift and broadening characteristics, extraction of the Doppler-broadened spectral component from LIF spectra is essential, a process necessitating deconvolution techniques. Compared with conventional methods, blind deconvolution dispenses with the prior acquisition of the cold plasma spectral line shape, avoiding complex modeling of hyperfine structure and natural broadening, and remains independent of magnetic field strength data at the measurement location. This paper proposes a blind deconvolution algorithm based on Wiener filtering and least-squares minimization, enabling direct extraction of the pure Doppler-broadened spectrum from observed LIF spectra. We systematically investigate the influence of two regularization parameters on the deconvolution results and establish practical guidelines for parameter selection. Experimental validation with measured Hall thruster LIF spectra shows that, compared to conventional Gaussian deconvolution filters and maximum entropy methods, this algorithm achieves equivalent Doppler-broadened spectrum extraction accuracy while eliminating the need for spectral pre-modeling.