Autonomous Guidance, Navigation, and Control for Close Formations Through Sequential Convex Programming and Inter-Satellite Ranging

Le résumé fourni par la source

A trending topic for future space missions is to distribute complex tasks among several agents, instead of relying on large monolithic spacecraft.In these scenarios, the acquisition and maintenance of the formation geometry becomes a critical aspect to be addressed that cannot be solved with traditional ground-based techniques.Hence, the development of novel and autonomous guidance, navigation, and control methods plays a driving role in enabling such mission concepts.In this paper, distributed algorithms are explored to accomplish both tasks in an organic and cooperative manner, trying to investigate all the key challenges of the problem.An innovative strategy for the relative state estimation and control of large spacecraft formations is proposed, based on a convex model predictive control strategy and radio-frequency navigation via inter-satellite link.More in detail, the guidance and control of the distributed system are addressed with sequential convex programming techniques that allow the computation of optimal control profiles for the formation considering goal-oriented objectives and safety-related constraints in a computationally efficient algorithmic routine.On the other hand, the selected navigation technique exploits a radio-frequency network architecture established between agents based on code division multiple access.Range measurements obtained through a GNSS-like signal transmitted by each agent are simulated.A real-time estimate of the formation state can thus be obtained with an increase in accuracy with respect to only using ECI-based measurements by GNSS sensors.The proposed distributed design optimizes the time and fuel spent by each agent for formation acquisition and keeping while retaining with higher fidelity the features of the problem like noisy, asynchronous measurement collection.

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