Accurate atmospheric wind field measurements are critical for understanding global climate dynamics and facilitating space exploration. Doppler asymmetric spatial heterodyne interferometer (DASH) is used to measure atmospheric wind speed through detecting the phase changes in interferograms induced by Doppler shifts of airglow emission lines. However, environmental temperature fluctuations and mechanical vibrations often cause imaging plane to shift, thereby introducing phase deviations, and degrading the measurement accuracy. In this study, a novel method of monitoring global fitting-based imaging shift is proposed. By etching periodic notches on the diffraction grating surface, the method models and fits the notch patterns formed on the detector plane to achieve precise imaging shift detection and correction. The optimization of notch signal modeling significantly reduces the number of fitting parameters, thus improving computational efficiency and detection precision. Through extensive simulations, the influences of signal-to-noise ratio (SNR) and model parameter variation on detection accuracy are analyzed. The results indicate that when the SNR exceeds 11, the detection uncertainty is still below 6.5 nm. Sensitivity analysis reveals that the detection error stays within acceptable limits when the variations of notch number and notch width are controlled within 40% and 0.7%, respectively, while the influence of edge smoothness parameter of notch pattern is negligible. To validate the performance of the method, the thermal stability is tested by using a near-infrared DASH prototype. The experimental results demonstrate a strong correlation between interferogram phase shifts, imaging plane shifts, and environmental temperature variations. After applying the proposed correction method, local phase fluctuations in the interferogram are significantly reduced, thus the phase stability is improved. Further, artificially applied imaging shifts are accurately detected with errors consistently below 9.96 nm, thereby confirming the reliability and precision of this method. All in all, the proposed method effectively detects and corrects the imaging plane shifts caused by temperature variations, enhancing interferogram phase stability and ensuring high-precision wind speed measurements. This method provides a robust and computationally efficient solution for reducing imaging shifts in DASH systems, and has great potential applications in atmospheric wind field measurement and space-based observation.
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