Thermal imaging drift monitoring of Doppler asymmetricspatial heterodyne spectroscopy for wind measurementbased on segmented edge fitting

Doppler asymmetric spatial heterodyne spectroscopy is recently developed for spaceborne measurement ofmiddle and upper atmospheric wind field, which relies on the accurate inverse of interferogram phase tocalculate the Doppler shift of airglow emission lines. The change of temperature leads the optical andmechanical components to thermally deformed, causing the imaging plane to thermally drift relative to thedetector, changing the distribution of interferogram phase on pixels, and directly introducing phase errors toaffect the wind speed inversion. In order to reduce the influence of imaging thermal drift on phase inversion, thesegmented fitting method is used in this paper to detect the sub-pixel edges of notch patterns and monitorimaging thermal drift accordingly. In the thermal stability test of a near-infrared Doppler asymmetric spatialheterodyne interferometer prototype, the thermal imaging drifts and ambient temperature show a highconsistency in the trend of high-frequency oscillation, and the correlation coefficient can reach 0.86 afterremoving the baseline. After phase correct by using the thermal imaging shift, the high-frequency oscillation ofinterferogram phase shift is also greatly suppressed. In order to further verify the accuracy of the algorithm, theinfluence of the data signal-to-noise ratio and the data distribution characteristic parameter errors used in thefitting on the edge detection are simulated. The results show that the edge detection accuracy is restrictedmainly by the data signal-to-noise ratio and the accuracy of the fringe frequency parameters. When the error ofthe fringe frequency parameter used for fitting is less than 0.5%, the error of other data distributioncharacteristic parameters is less than 5%, and the data signal-to-noise ratio is enhanced more than 35 times, thealgorithm in this paper can achieve a detection accuracy higher than 0.05 pixels