A Graph Convolutional Network Framework for Area Attention and Tracking Compensation of In-Orbit Satellite

In order to solve the problems of low tracking accuracy of in-orbit satellites by ground stations and slow processing speed of satellite target tracking images, this paper proposes an orbital satellite regional tracking and prediction model based on graph convolutional networks (GCNs). By performing...

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Bibliographic Details
Main Authors: Shuai Wang, Ruoke Wu, Yizhi Jiang, Xiaoqiang Di, Yining Mu, Guanyu Wen, Makram Ibrahim, Jinqing Li
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/15/12/6742
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