Spacecraft Autonomous Navigation Technologies Based on Multi-source Information Fusion
This book introduces readers to the fundamentals of estimation and dynamical system theory and their applications in multi-source information-fusion 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. The book bridges the gap between theory and practice by concentrating on the relationships between estimation theory and autonomous navigation systems for spacecraft. There are also a lot of useful formulas and different types of estimators to help readers understand basic estimation ideas and give them a quick reference guide.
Spacecraft Autonomous Navigation Technologies Based on Multi-source Information Fusion PDF Free Download
Author(s): Dayi Wang, Maodeng Li, Xiangyu Huang, Xiaowen Zhang
Series: Space Science and Technologies
Publisher: Springer, Year: 2020