LEO Satellite Track Correction for CSST Multi-Band Imaging Data
Huai-Jin Tang, Xiao-Lei Meng, Hu Zhan, Guo-Liang Li, Cheng-Liang Wei, Xian-Min Meng, Xi-Yang Fu, You-Hua Xu

TL;DR
This paper develops a method to reconstruct and correct satellite trail contamination in multi-band images from the CSST, significantly reducing affected sources especially in the NUV and i bands, considering realistic satellite parameters.
Contribution
It introduces an improved simulation and trail correction method that accounts for multi-band observational conditions and satellite parameters, enhancing contamination mitigation for CSST data.
Findings
Over 50% reduction in affected sources in NUV band after correction.
More than 30% reduction in affected sources in i band.
Correction effectiveness varies with spectral band, satellite altitude, and brightness model.
Abstract
Low Earth Orbit satellite (LEOsat) mega-constellations are considered to be an unavoidable source of contamination for survey observations to be carried out by the China Space Station Telescope (CSST) over the next decade. This study reconstructs satellite trail profiles based on simulated parameters, including brightness levels and orbital altitudes, in combination with multi-band simulated images. Compared to our previous work, the simulated images in this study more accurately replicate the realistic observational conditions of CSST and extend beyond single-band analysis. Variations in LEOsat trail brightness, source brightness, background noise, and source density across different bands result in differing levels of accuracy in trail reconstruction and subsequently affect the reliability of photometric measurements. The reconstructed trail profiles are subsequently applied to…
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Taxonomy
TopicsCalibration and Measurement Techniques · Space Satellite Systems and Control · Satellite Communication Systems
