Phase Error Correction of Spatial Heterodyne Spectrometer

Hailiang, 施海亮 Shi; Wei, 熊伟 Xiong; Zhiwei, 李志伟 Li; Haiyan, 罗海燕 Luo

doi:10.3788/aos201333.0330003

Cited by 1 publication

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“…This paper, based on the physical model of the SHS detection system, establishes a numerical simulation model for SHS's interference images. By introducing a fixed phase error based on the correlation between phase error and its interference image [9], a simulation of zero optical path point and adjacent saturation interference images is created. Exploiting the property of phase error stability, a cost function for phase error before and after interferogram saturation is established, and finally, an optimal solution is obtained using the particle swarm algorithm (PSO) [10] to correct partially saturated interference data.…”

Section: Introductionmentioning

confidence: 99%

Research on correction method of saturation interference data of space heterodyne spectrometer

Zhang,

Li,

Luo

et al. 2024

Fifth International Conference on Optoelectronic Science and Materials (ICOSM 2023)

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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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Section: Introductionmentioning

confidence: 99%