Earth Observation Satellites -  Hao Chen,  Chun Du,  Jun Li,  Shuang Peng

Earth Observation Satellites (eBook)

Task Planning and Scheduling
eBook Download: PDF
2023 | 1st ed. 2023
XII, 189 Seiten
Springer Nature Singapore (Verlag)
978-981-99-3565-9 (ISBN)
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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 the help 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.



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.

 



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.
Erscheint lt. Verlag 4.9.2023
Zusatzinfo XII, 189 p. 76 illus., 67 illus. in color.
Sprache englisch
Original-Titel Dui Di Guan Ce Wei Xing Ren Wu Gui Hua Yu Diao Du Ji Shu
Themenwelt Naturwissenschaften Physik / Astronomie Astronomie / Astrophysik
Naturwissenschaften Physik / Astronomie Festkörperphysik
Technik Elektrotechnik / Energietechnik
Technik Fahrzeugbau / Schiffbau
Technik Luft- / Raumfahrttechnik
Schlagworte Genetic algorithm for satellite • Image satellite scheduling • Multi agent system model • Satellite autonomous scheduling • Satellite distributed scheduling • Satellite onboard scheduling • satellite range scheduling • Satellite scheduling • Satellite task scheduling
ISBN-10 981-99-3565-2 / 9819935652
ISBN-13 978-981-99-3565-9 / 9789819935659
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