Optimal guidance and decentralised state estimation applied to a formation flying demonstration mission in GTO

An integrated approach to guidance, navigation and control (GNC) of formation flying spacecraft (sc) is introduced. The design process considers a three-sc mission in a reference geostationary transfer orbit (GTO). A detailed definition of the mission framework, in terms of GNC modes and corresponding science and technology requirements, is provided. This, together with an analysis of the dynamic environment of the mission, establishes inputs to the design of a low-thrust optimal relative configuration that minimises the fuel consumption and overall complexity. The obtained solution is assessed in detail by means of an analysis considering perturbations acting over a sc in Earth GTO. The GNC closed loop uses the results of the mission analysis and design process as specifications. An algebraic closed-loop algorithm is proposed for the guidance and control (GC) subsystem, minimising the propellant consumption and ensuring collision avoidance. Using Pontryagin's maximum principle, the GC algorithm provides the optimal trajectories from the current state until the target state, as well as the optimal control inputs to follow these trajectories. A full-order decentralised filter implements the navigation algorithm. It estimates the full state of the involved sc and is based on an extended Kalman filter (EKF) for local measurements, and on a covariance intersection (CI) algorithm (plus the EKF prediction part) for the fusion between local state estimates and state estimates communicated by other sc. Results of applying the GNC algorithms to a realistic simulation of the specified mission are presented. The main original contribution of the work presented here is the design of the formation flying mission and algorithms using a top-down approach. From a requirement to maximise the time which can be used for experimentation at the apogee, the orbits of the three sc, as well as the propellant optimal manoeuvres for formation (re)acquisition, have been determined. A novel approach to the Cl method has been used to estimate the relative positions between sc. The algorithms have been implemented and tested in an end-to-end mission simulation tool.