Guidance, Navigation and Control Algorithms for Satellite Formation Flying (2nd Edition)

A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Astronautics & Space Science".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 1369

Special Issue Editors


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Guest Editor
Department of Aerospace Science and Technology, Politecnico di Milano, 20156 Milan, Italy
Interests: development of AOCS/GNC algorithms; simulation systems; flight software for autonomous formation flying and proximity operation applications
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Guest Editor
ClearSpace SA, Rue de Lausanne 64, 1020 Renens, Switzerland
Interests: GNC; onboard autonomy; precise navigation; rendezvous; formation-flying
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Special Issue Information

Dear Colleagues,

We can announce the second edition of the Special Issue of the MDPI open access journal Aerospace, titled “Guidance, Navigation and Control Algorithms for Satellite Formation Flying (2nd Edition)”.

Formation flying missions enable technological applications of scientific and societal relevance where standard monolithic solutions fail. Distributed space systems, swarms, and fractionated systems are a key asset for building extended, flexible, and scalable space endeavors. Moreover, a significant number of current technological research efforts address multi-satellite missions devoted to in-orbit servicing, assembly, manufacturing and recycling, as well as active debris removal activities.

The operation of satellites in proximity, with different levels of cooperation/collaboration among them, demands the development of relative guidance, navigation and control (GNC) systems, which offer all the functions that complement the standard orbit/attitude determination and control tasks of single-satellite missions. In addition, mission safety for collision avoidance among the spacecraft of the formation must be ensured. Frontier research efforts for developing relative GNC algorithms focus on improving navigation/control performances, increasing the level of autonomy and minimizing the computational load while ensuring robust and reliable approaches suitable for spaceborne implementation.

This Special Issue will collect contributions covering a range of aspects related to GNC systems, ranging from relative navigation and establishing and maintaining the required relative configuration between the elements of a space distributed system to collision avoidance monitoring and maneuvering. Particular attention will be devoted to algorithms’ development and verification. Potential applications include, but are not limited to, the following:

  • Formation flying missions for Earth observation;
  • Formation flying missions for space observation;
  • In-orbit servicing, assembly, manufacturing, and recycling missions;
  • In-orbit inspection and active debris removal missions;
  • Swarms missions;
  • Formation flying missions around small bodies.

Dr. Gabriella Gaias
Dr. Jean-Sébastien Ardaens
Guest Editors

Manuscript Submission Information

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Keywords

  • relative navigation
  • relative orbit determination
  • spacecraft rendezvous
  • satellite formation flying
  • formation reconfiguration
  • active debris removal
  • autonomy
  • swarms
  • distributed space systems

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Related Special Issue

Published Papers (3 papers)

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34 pages, 14457 KB  
Article
A Finite State Machine Guidance Architecture for Autonomous Rendezvous with Arbitrarily Elliptic Targets
by Diego Buratti, Gabriella Gaias, Stefano Torresan, Thomas Vincent Peters and Pedro Roque
Aerospace 2026, 13(3), 230; https://doi.org/10.3390/aerospace13030230 - 1 Mar 2026
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Abstract
This paper details the design of a guidance architecture, in the form of a layered, finite state machine, meant to enable safe and autonomous rendezvous operations. The onboard software uses relative state parametrization based on relative orbital elements which provide significant geometrical insight [...] Read more.
This paper details the design of a guidance architecture, in the form of a layered, finite state machine, meant to enable safe and autonomous rendezvous operations. The onboard software uses relative state parametrization based on relative orbital elements which provide significant geometrical insight into the shape of the relative orbit. The development is structured in two main steps: first, novel closed-form impulsive control schemes, derived from the Gauss Variational Equations expressed in a velocity-aligned frame, are formulated. These complement available strategies from the literature and generalize them for arbitrarily eccentric reference orbits. Secondly, the definition of the guidance layer provides the chaser spacecraft with the capability to select, schedule, and execute the proper maneuvers to complete a given rendezvous scenario, ensuring operational safety and predictability. The functionality and performance of the implemented architecture are analyzed through numerical tests in a linear propagator and a high-fidelity non-linear simulator. The results provide validation of the developed maneuvers’ strategies, as well as demonstrating how the proposed guidance architecture can be used in a straightforward fashion across different target orbit scenarios, while guaranteeing the same level of passive safety. Full article
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19 pages, 2010 KB  
Article
Decoupling Global and Local Faults in Satellite Swarms Using Smart-Freeze Adaptation and Isolation-Priority Logic
by Mahsa Azadmanesh, Krasin Georgiev, Stanyo Kolev and Michael Todorov
Aerospace 2026, 13(2), 176; https://doi.org/10.3390/aerospace13020176 - 13 Feb 2026
Viewed by 294
Abstract
Satellite swarm operations require robust methodologies to distinguish between leader-induced reference frame biases (global errors) and individual follower anomalies (local deviations). This is the challenge of distributed fault diagnosis. In leader–follower topologies, distinguishing between a global reference error (leader satellite broadcasting incorrect navigation [...] Read more.
Satellite swarm operations require robust methodologies to distinguish between leader-induced reference frame biases (global errors) and individual follower anomalies (local deviations). This is the challenge of distributed fault diagnosis. In leader–follower topologies, distinguishing between a global reference error (leader satellite broadcasting incorrect navigation data) and a local node error (follower satellite drifting) is mathematically ambiguous when we use standard methods. Even recent unsupervised frameworks, such as Model-Guided Online Transfer Learning (MGOTL), that excel at single-satellite component diagnosis, suffer from adaptation and signal bleed when they are applied directly to distributed topologies. Therefore, we propose the Isolation-First Consensus Anomaly Detection (IF-CAD) framework for Decoupling Global and Local Faults in Satellite Swarms. We introduce a Smart Freeze mechanism to prevent the learning of persistent faults and a hierarchical logic that prioritizes local isolation over global agreement. The IF-CAD framework successfully decouples global leader faults from local follower faults. Fault detection remains stable even during long-duration anomalies. Full article
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25 pages, 1185 KB  
Article
Analysis of a Rigid-Body Pose Estimator for Relative Spacecraft Navigation
by Caitong Peng and Daniel Choukroun
Aerospace 2026, 13(1), 25; https://doi.org/10.3390/aerospace13010025 - 26 Dec 2025
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Abstract
This study presents a rigorous error analysis of a previously published estimator that determines the single-frame relative pose of two rigid bodies from batches of point and unit vector measurements. The estimator solves a constrained least-squares optimization problem where the pose is represented [...] Read more.
This study presents a rigorous error analysis of a previously published estimator that determines the single-frame relative pose of two rigid bodies from batches of point and unit vector measurements. The estimator solves a constrained least-squares optimization problem where the pose is represented by a dual quaternion and the properties of pose dual quaternions are exactly satisfied. We develop an eigenvalue-based error analysis and derive analytical expressions for the three-dimensional attitude and translation errors, along with their means and covariance matrices. The closed-form formulas provide significant insights into the distinctive impacts of the point and vector observations’ geometry and noise. They provide valuable tools for performance analysis and prediction. We consider noises both in the body frame and in the reference frame observations. Extensive Monte-Carlo simulations validate the accuracy and consistency of these formulas. Furthermore, we investigate the algorithm’s sensitivity to variations in the number of observations and in the observations’ weight coefficients of the cost function. Full article
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