Forward Modeling of Dust-Induced Stray Light in Ground-Based Coronagraphs: A Dual-Path Monitoring Approach for High-Precision Inner Corona Observations
Xiande Liu, Xuefei Zhang, Yu Liu, Tengfei Song, Mingyu Zhao, Mingzhe Sun, Feiyang Sha, and Jun Fang

TL;DR
This paper introduces a dual-path real-time correction method for dust-induced stray light in ground-based coronagraphs, significantly improving the quality of inner corona observations and enabling more accurate solar studies.
Contribution
The authors develop a novel physical modeling and monitoring approach that effectively reduces stray light, enhancing the fidelity of ground-based coronal imaging.
Findings
RMS noise in polar background reduced by ~67% after correction.
Signal-to-background ratio improved by up to 3.7 times under heavy contamination.
Corrected images accurately recover coronal structures and plasma temperature.
Abstract
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…
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