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Beschreibung
This book introduces readers to the application of orbital data on space objects in the contexts of conjunction assessment and space situation analysis, including theories and methodologies. It addresses the main topics involved in space object conjunction assessment, such as: orbital error analysis of space objects; close approach analysis; the calculation, analysis and application of collision probability; and the comprehensive assessment of collision risk. In addition, selected topics on space situation analysis are also presented, including orbital anomaly and space event analysis, and so on.
The book offers a valuable guide for researchers and engineers in the fields of astrodynamics, space telemetry, tracking and command (TT&C), space surveillance, space situational awareness, and space debris, as well as for graduates majoring in flight vehicle design and related fields.
This book introduces readers to the application of orbital data on space objects in the contexts of conjunction assessment and space situation analysis, including theories and methodologies. It addresses the main topics involved in space object conjunction assessment, such as: orbital error analysis of space objects; close approach analysis; the calculation, analysis and application of collision probability; and the comprehensive assessment of collision risk. In addition, selected topics on space situation analysis are also presented, including orbital anomaly and space event analysis, and so on.
The book offers a valuable guide for researchers and engineers in the fields of astrodynamics, space telemetry, tracking and command (TT&C), space surveillance, space situational awareness, and space debris, as well as for graduates majoring in flight vehicle design and related fields.
Über den Autor
Shaoxu Song is an Associate Professor in the School of Software at Tsinghua University in Beijing, China. His research interests include data quality and data integration. He has published more than 50 papers in top conferences and journals such as SIGMOD, VLDB, ICDE, ACM TODS, VLDBJ, IEEE TKDE, etc. He served as a Vice Program Chair for the 2022 IEEE International Conference on Big Data (IEEE BigData 2022) and received the Distinguished Reviewer award from VLDB 2019 and an Outstanding Reviewer award from CIKM 2017.
Lei Chen is a Chaired Professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology and the Director of the HKUST Big Data Institute. He received the SIGMOD Test-of-Time Award in 2015 and served as the Program Committee Co-Chair of VLDB 2019 and ICDE 2023. He is currently the Editor-in-Chief of the VLDB Journal, and the Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (TKDE). He is an IEEE Fellow and ACM Distinguished Scientist.
Zusammenfassung

Presents value-added algorithms for essential orbital data

Covers nearly every aspect of the conjunction assessment issue, as well as selected aspects of space situation analysis

Includes detailed formulae and techniques to support engineers' daily work

Includes supplementary material: [...]

Inhaltsverzeichnis
Introduction.- Orbital Prediction Error Propagation of Space Objects.- Orbital Error Analysis Based on Historical Data.- Close Approach Analysis between Space Object.- Calculation of Collision Probability.- Application of Collision Probability.- Orbital Anomaly and Space Events Analysis.- Environment and Flux Analysis of Space Debris.
Details
Erscheinungsjahr: 2018
Fachbereich: Raumfahrttechnik
Genre: Importe, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xxiv
318 S.
61 s/w Illustr.
115 farbige Illustr.
318 p. 176 illus.
115 illus. in color.
ISBN-13: 9789811097522
ISBN-10: 9811097526
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Chen, Lei
Bai, Xian-Zong
Liang, Yan-Gang
Li, Ke-Bo
Auflage: Softcover reprint of the original 1st edition 2017
Hersteller: Springer
Springer Singapore
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 235 x 155 x 19 mm
Von/Mit: Lei Chen (u. a.)
Erscheinungsdatum: 05.07.2018
Gewicht: 0,522 kg
Artikel-ID: 114110623

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