Jet Transport Technique: Theory and Application

Preface
Contents
1 Introduction
	1.1 Jet Transport Technique
	1.2 Organization of the Book
	References
2 The Implementation of Jet Transport Software
	2.1 Polynomial Storage
	2.2 Polynomial Algebra
		2.2.1 Basic Polynomial Operations
		2.2.2 Differential Polynomial Algebra
		2.2.3 Polynomial Approximation to Univariate Functions
		2.2.4 Polynomial Approximation to a Multi-variable Function
		2.2.5 Numerical Simulations
	2.3 Flow Propagation
		2.3.1 Parameterization Method
		2.3.2 Runge-Kutta Methods
		2.3.3 Semi-analytical Polynomial Propagation
		2.3.4 Polynomial Evaluation
		2.3.5 Numerical Simulations
	References
3 Analysis of Orbit Uncertainty Propagation Using Jet Transport
	3.1 Executive Summary
	3.2 Dynamical Models
		3.2.1 Cartesian Dynamic Model
		3.2.2 Cylindrical Coordinates
		3.2.3 GEO Dynamical Model
		3.2.4 Coordinate Transformations
	3.3 Analysis of Dominant Perturbation Accelerations
		3.3.1 Perturbation Modelling
		3.3.2 Perturbation Analysis
	3.4 Geostationary Orbit Propagation
		3.4.1 Selection of Fixed Step Integrator
		3.4.2 Polynomial-Based Orbit Propagation
		3.4.3 Comparison with Different Coordinate Representations
	References
4 Jet Transport Application to Particle Filter for Attitude Estimation  of Tumbling Space Objects
	4.1 Executive Summary
	4.2 Basic Dynamical Models
	4.3 Quaternion Particle Filter
	4.4 Jet Transport Particle Filter
	4.5 Simulation Studies
		4.5.1 Simulation Scenarios
		4.5.2 Simulation Results
	References
5 Jet Transport-Based High Order Kalman Filter for Joint Orbit and Parameter Estimation
	5.1 Executive Summary
	5.2 Augmented High Order Extended Kalman Filter
	5.3 Joint Orbit and Parameter Estimation
		5.3.1 Equations of Motion
		5.3.2 Measurement Model
		5.3.3 Case A: Spacecraft State and Physical Parameter Estimation
		5.3.4 Case B: Spacecraft State and Tracking Station Position Estimation
		5.3.5 Evaluation Metrics
	5.4 Numerical Simulations
		5.4.1 Spacecraft Physical Parameter Estimation
		5.4.2 Tracking Station Position Estimation
	References
6 Autonomous Orbit Determination and Fault-Tolerant Designs Using Jet Transport
	6.1 Executive Summary
	6.2 Standard High Order Extended Kalman Filter
	6.3 Fault-Tolerant Variants of the JT-HEKF-bold italic nn Filter
		6.3.1 Fault Measurement Detection
		6.3.2 False Measurement-Discarding Based JT-HEKF-bold italic nn Filter
		6.3.3 Single and Multiple Scale Factor Based JT-HEKF-bold italic nn Filter
	6.4 Model Description
		6.4.1 Equations of Motion
		6.4.2 Measurement Model
	6.5 Numerical Simulations
		6.5.1 Autonomous Nonlinear Orbit Determination
		6.5.2 Autonomous Fault-Tolerant Orbit Determination
	References
7 Jet Transport-Based Adaptive Order-Switching Filter
	7.1 Executive Summary
	7.2 Order-Switching Based JT-HEKF-nn Filter
		7.2.1 Design of the Adaptive Order-Switching Strategy
		7.2.2 Detailed Implementation of A JT-OSHEKF-bold italic nn Filter
	7.3 Model Description
		7.3.1 Equations of Motion
		7.3.2 Measurement Model
	7.4 Numerical Simulations
		7.4.1 Case Study A: Adverse Simulation Scenario
		7.4.2 Case Study B: Mild Simulation Scenario
	References
8 Low-Thrust Station Keeping at Libration Point Orbits Using Jet Transport
	8.1 Executive Summary
	8.2 Equations of Motion
	8.3 Geometric Structure Around Halo Orbits
	8.4 Station-Keeping Strategies
		8.4.1 Limit Impulsive Control Laws
		8.4.2 Dynamical Reshaping Control Laws
		8.4.3 Geometric Analysis of the Limit Impulsive Control Laws
	8.5 Numerical Simulations
		8.5.1 Stability of the Control Laws
		8.5.2 Long-Term and Geometric Behavior of the Controlled System
		8.5.3 Robustness of the Control Laws to Navigation Errors
		8.5.4 Control Cost Estimations
		8.5.5 A Note on A HSP Control Law
	References