Saved in:
Bibliographic Details
Main Authors: Liu, Xiande, Zhang, Xuefei, Liu, Yu, Song, Tengfei, Zhao, Mingyu, Sun, Mingzhe, Sha, Feiyang, Fang, Jun
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2605.12979
Tags: Add Tag
No Tags, Be the first to tag this record!
Table of Contents:
  • High-precision ground-based observations of the inner corona (1.05-2.0 R_sun) are fundamentally constrained by instrumental stray light, particularly the additive background from dynamic dust accumulation on the objective lens. To address this issue, we propose a correction method for the Spectral Imaging Coronagraph (SICG) based on dual-path real-time monitoring and forward physical modeling. By simultaneously imaging the objective lens surface, we obtain deterministic prior information on dust distribution. We construct a physical point-spread function using optical defocus parameters and reconstruct the nonuniform scattering background via convolution. Model parameters are retrieved through data-driven inversion constrained by polar coronal holes. The method demonstrates excellent robustness under varying contamination conditions. After correction, the rms noise in the polar background is reduced by approximately 67% on average, and the signal-to-background ratio improves by a factor of up to 3.7 under heavy contamination conditions. Comparisons with space-based Solar Dynamics Observatory/Atmospheric Imaging Assembly observations indicate that the corrected images recover the morphological structures of streamers with high fidelity. Further radial intensity analysis reveals that the correction process successfully restores the hydrostatic exponential decay characteristic of inner coronal radiation. The fitted decay coefficient corresponds to a plasma temperature of approximately 2.0 MK, consistent with the characteristic formation temperature of the Fe XIV 530.3 nm line. These results demonstrate that the method effectively eliminates the dominant systematic bias in ground-based observations, providing a reliable data foundation for high-precision coronal thermodynamic and dynamic research with the SICG.