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.       

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.

This book is to design, implement, test and cryptanalyze three stream ciphers that are based on the multi-map orbit hopping mechanism (Mmohom), a generic method to design stream ciphers. Mmohocc, multi-map orbit hopping chaotic cipher: chaos has been connected to cryptography due to its confusion and diffusion, the two important properties of a secure cipher. We apply Mmohom to multiple chaotic systems to construct Mmohocc, which greatly accelerates chaos behavior and makes chaos more suitable for cryptographic purposes. The keystreams have passed two batteries of the most popular and stringent statistical tests. Cryptanalysis shows that Mmohocc is resistant against known attacks. Mmohom-LFSR-based cipher: Mmohom is used in conjunction with multiple LFSRs (Linear Feedback Shift Register) to destroy the linearity of LFSRs. Cryptanalysis against algebraic attack is discussed. Mmohoct, multi-map orbit hopping cipher by T- functions: the T-function has maximal single cycle property; meanwhile it has some undesired algebraic patterns. We introduce the Mmohom to destroy the unwanted properties and build two experimental Mmohoct ciphers.