The spatial heterodyne spectroscopy (SHS) technique comprehensively integrates the principles of grating diffraction and spatial interference, enabling the detection of activities with high resolution and signal-to-noise ratio, which is adopted for high-precision remote sensing of atmospheric composition. SHS employs a focal plane array detector to simultaneously record the interference information of different optical path differences. When detecting continuous intense light signals, due to the limitations of interference modulation and the dynamic response range of the detector, the interference zero optical path point and its adjacent pixels become saturated. Directly recovering the spectrum from the saturation interferogram can lead to significant deviations from the theoretical spectrum. Base on the imaging principle of SHS, a simulation model was established for the interference data saturation of the zero optical path point and its vicinity, and used to analyse the influence of phase error on interference data. Utilizing the property of invariant phase error in SHS, a particle swarm algorithm (PSO) is employed to calibrate the intensity values of the saturation interference data. The results indicate that the proposed algorithm can reduce the normalized root-mean-square error of the recovered spectrum from 5.01e-2 to 2.10e-3.
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