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Earth Observation Satellites: Task Planning and Scheduling

Autor Hao Chen, Shuang Peng, Chun Du, Jun Li
en Limba Engleză Hardback – 5 sep 2023
This book highlights the practical models and algorithms of earth observation satellite (EOS) task scheduling. EOS task scheduling is a typical complex combinatorial optimization problem with NP-Hard computational complexity. It is a key technology in aerospace scheduling and has attracted global attention. Based on the actual needs of the EOS operation control center, the book summarizes and reviews the state of the art in this research and engineering field. In both deterministic scenarios and dynamic scenarios, the book elaborates on the typical models, algorithms, and systems in centralized, distributed, and onboard autonomous task scheduling. The book also makes an outlook on the promising technologies for EOS task planning and scheduling in the future. It is a valuable reference for professionals, researchers, and students in satellite-related technology. 


This book is a translation of an original Chinese edition. The translation was done with thehelp of artificial intelligence. A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.

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Specificații

ISBN-13: 9789819935642
ISBN-10: 9819935644
Pagini: 189
Ilustrații: XII, 189 p. 76 illus., 67 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.5 kg
Ediția:1st ed. 2023
Editura: Springer Nature Singapore
Colecția Springer
Locul publicării:Singapore, Singapore

Cuprins

1. Introduction.- 2. Problem description and analysis of EOS task scheduling.- 3. Model and method of ground centralized EOS task scheduling.- 4. EOS Task rescheduling for dynamic factors.- 5. Model and method of ground distributed EOS task scheduling.- 6. Model and method of EOS onboard autonomous task scheduling.- 7. Satellite task scheduling system.- 8. Summary and prospect.

Notă biografică

Hao Chen
Dr. Hao Chen is currently a professor at the National University of Defense Technology, China. His research interests include data mining, machine learning, and evolutionary computation. 
Shuang Peng
Dr. Shuang Peng is currently an assistant professor at the National University of Defense Technology, China. His research interests include satellite intelligent scheduling, machine learning, and evolutionary computation.  Chun Du
Dr. Chun Du is currently an associate professor at the National University of Defense Technology, China. His research interests include machine learning, machine vision, and remote sensing.
 
Jun Li Dr. Jun Li is currently a professor at the National University of Defense Technology, China. His research interests include management and analysis of big data, and spatial information system.
 


Textul de pe ultima copertă

This book highlights the practical models and algorithms of earth observation satellite (EOS) task scheduling. EOS task scheduling is a typical complex combinatorial optimization problem with NP-Hard computational complexity. It is a key technology in aerospace scheduling and has attracted global attention. Based on the actual needs of the EOS operation control center, the book summarizes and reviews the state of the art in this research and engineering field. In both deterministic scenarios and dynamic scenarios, the book elaborates on the typical models, algorithms, and systems in centralized, distributed, and onboard autonomous task scheduling. The book also makes an outlook on the promising technologies for EOS task planning and scheduling in the future. It is a valuable reference for professionals, researchers, and students in satellite-related technology. 


This book is a translation of an original Chinese edition. The translation was done with thehelp of artificial intelligence. A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.

Caracteristici

Reviews advances of task scheduling technology of earth observation satellites Includes latest practical models and algorithms Provides various approaches for different scenarios