Spacecraft Autonomous Navigation Technologies Based on Multi-source Information Fusion (Hardcover, 1st ed. 2021)

This book introduces readers to the fundamentals of estimation and dynamical system theory, and their applications in the field of multi-source information fused autonomous navigation for spacecraft. The content is divided into two parts: theory and application. The theory part (Part I) covers the mathematical background of navigation algorithm design, including parameter and state estimate methods, linear fusion, centralized and distributed fusion, observability analysis, Monte Carlo technology, and linear covariance analysis. In turn, the application part (Part II) focuses on autonomous navigation algorithm design for different phases of deep space missions, which involves multiple sensors, such as inertial measurement units, optical image sensors, and pulsar detectors. By concentrating on the relationships between estimation theory and autonomous navigation systems for spacecraft, the book bridges the gap between theory and practice. A wealth of helpful formulas and various types of estimators are also included to help readers grasp basic estimation concepts and offer them a ready-reference guide.       

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Space Science and Technologies
Release date:	August 2020
First published:	2021
Authors:	Dayi Wang • Maodeng Li • Xiangyu Huang • Xiaowen Zhang
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	340
Edition:	1st ed. 2021
ISBN-13:	978-981-15-4878-9
Subtitles:	Chinese
Categories:	Books > Professional & Technical > Other technologies > General Books > Professional & Technical > Transport technology > Aerospace & aviation technology > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
LSN:	981-15-4878-1
Barcode:	9789811548789

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