Earth Observation Satellites: Task Planning and Scheduling - Softcover

Chen, Hao; Peng, Shuang; Du, Chun; Li, Jun

Softcover

ISBN 10: 9819935679 ISBN 13: 9789819935673

Verlag: Springer, 2024

Inhaltsangabe

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.

Über diesen Titel

Über die Autorin bzw. den Autor

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.

 

Von der hinteren Coverseite

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.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2024
• Sprache: Englisch
• ISBN 10: 9819935679
• ISBN 13: 9789819935673
• Einband: Taschenbuch
• Anzahl der Seiten: 201
• Kontakt zum Hersteller: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Deutschland