Correction of Atmospheric Model Through Data Mining With Historical Data of Two-Line Element

Correction of Atmospheric Model Through Data Mining With Historical Data of Two-Line Element

The existing atmospheric mass density models (AMDM) would produce considerable errors in orbital prediction for Low Earth Orbit (LEO) satellites. In order to reduce these errors and correct the AMDM, this paper presents methods based on data mining with historical data of two-line element (TLE). Sta...

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Bibliographic Details
Main Authors: Xue Bai, Chuan Liao, Ming Xu, Yaru Zheng
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Data mining
atmospheric mass density model
random forest
artificial neural network
support vector machine
two-line element
Online Access:https://ieeexplore.ieee.org/document/9134447/

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