期刊
REMOTE SENSING
卷 15, 期 19, 页码 -出版社
MDPI
DOI: 10.3390/rs15194718
关键词
ground-based observation; atmospheric turbulence; Low Earth Orbit object; Adaptive Optics; Singular Value Decomposition filtering
This paper addresses the challenges and proposes solutions for ground-based observation of Low Earth Orbit (LEO) targets. The study successfully improves image quality and tracks fast-moving objects using Adaptive Optics (AO) and post-processing techniques. The feasibility of continuous monitoring and tracking of objects is also demonstrated.
This paper addresses the challenges of ground-based observation of Low Earth Orbit (LEO) targets using on-Earth telescopes and proposes solutions for improving image quality and tracking fast-moving objects under atmospheric turbulence conditions. The study investigates major challenges, including atmospheric turbulence-induced aberrations, blurring, telescope platform vibrations, and spatial variations caused by the target motion. A scenario simulation is conducted considering practical limitations, such as feasible time slots for monitoring and the number of available frames within the Field of View (FoV). The paper proposes a novel method for detecting LEO targets using Harris corner features and matching adjacent images upon the corrected frames by Adaptive Optics (AO), with a 38% reduction in the Mean Squared Error (MSE) achieved for certain frames within the isoplanatic angle. Additionally, a refinement strategy for deblurring images is proposed, combining the post-processing with Singular Value Decomposition (SVD) filtering; with a proper filtering factor (beta=0.1), an almost complete collection of 14 corner nodes can be detected. The feasibility of continuously tracking objects with uncontrolled attitudes, such as space debris, is successfully demonstrated with continuous monitoring of certain features. The proposed methods offer promising solutions for ground-based observation of LEO targets, providing insights for further research and application in this field.
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