A PCA-SVM Regression Model for LEO Space Debris Orbit Prediction in an Optical Space-Based Space Surveillance Network-Reference-Cited by-同舟云学术

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A PCA-SVM Regression Model for LEO Space Debris Orbit Prediction in an Optical Space-Based Space Surveillance Network

Published:2024 Issue: Volume:12 Page:60447-60466
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hamidian Sara¹^ORCID,Kosari Amir Reza¹^ORCID

Affiliation:

1. Faculty of New Sciences and Technologies, School of Aerospace Engineering, University of Tehran, Tehran, Iran

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10508582.pdf?arnumber=10508582

Reference58 articles.

1. A novel high-precision observation mode for the tracking and imaging radar TIRA-principle and performance evaluation;Cerutti-Maori

2. Real-time space object tracklet extraction from telescope survey images with machine learning

3. Correlation and orbit determination of space objects based on sparse optical data

4. Innovative observing strategy and orbit determination for Low Earth Orbit space debris

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