Accepted Papers

Receiver Autonomous Integrity Monitoring for LEO Satellites: Outlier Detection and Exclusion

Adam Ghribi¹, Marvin B. Stucke¹, Thomas Hobiger¹, Stefan Winkler²

¹ Institute of Navigation, University of Stuttgart, Germany

² Airbus Defence and Space

Robust Precise Orbit Determination (POD) is essential for Low Earth Orbit (LEO)
satellite missions. Based on observational data from Global Navigation Satellite System (GNSS),
the orbit parameters are estimated by means of an adjustment process. To achieve accurate
results, highly reliable navigation data are required. In this work, we investigate the application
of Receiver Autonomous Integrity Monitoring (RAIM)-based methods — originally developed
for aviation — to detect and exclude faulty GNSS measurements in a post-processed POD
framework. Our approach utilizes redundant GNSS code measurements and evaluates the
residuals from a weighted least squares (WLSQ) orbit solution. Based on a predefined false
alarm rate, we set a threshold and compare it to a residual-based test statistic. The method
enables detection and exclusion of outliers in post-processed solutions. Simulation and real
GRACE-FO data results demonstrate the effectiveness of the applied RAIM-based method. It
enhances the integrity and reliability of GNSS-based POD solutions for LEO satellites.

Integrating High-Level Priority Decisions with Distributed Safety Filter for Multi-Satellite Collision Avoidance

Chengrui Shi¹, Tao Meng², Hang Zhou¹

¹ School of Aeronautics and Astronautics, Zhejiang University, Hangzhou, China

² Huanjiang Laboratory, Zhuji, China

Miniaturization and dense constellation deployments exacerbate collision risks of future satellites.
While numerous collision avoidance strategies have been proposed, few reconcile agentlevel
safety with mission-level efficiency. In this paper, we propose a distributed inter-satellite
collision avoidance framework where low-level safety control is guided by high-level priority
decisions. First, we formulate “safe protocol” constraints among satellites and enforce these
constraints on nominal controllers through distributed safety filters, establishing collisionfree
coordination of the swarm. By introducing tunable priority parameters within the safety
filter, collision evasion responsibilities become dynamically adjustable, enabling swarm behavior
adaptation. We further demonstrate two methods to integrate with high-level decisions: using
optimization to approximate global reference behaviors and using Large Language Models to
accommodate to tasks, respectively. Theoretical analysis proves

Master Attitude Controller for Modular Laser Communication Systems

René Rüddenklau ^1,2, Hannes Zeihsel¹, Fabian Rein¹, Simon Spier¹, Jorge Rosano Nonay¹

¹German Aerospace Center (DLR), Institute of Communications and Navigation, Weßling, Germany

² Technische Universität Wien, Mechatronics and Power Electronics Institute (MPEI), Vienna, Austria

Space-based free-space optical communication requires precisely coordinating the
pointing of multiple subsystems. In order to manage the control interfaces and dynamics of
evolving actuators and sensors, and their design limitations, a dedicated control unit has been
developed and is presented in this work: the Master Attitude Controller. It facilitates integration
of the satellite’s attitude determination and control system with the optical communication
payload. Additionally, it incorporates an on-board inertial measurement unit to enhance the
accuracy of attitude knowledge during the acquisition phase. In the subsequent tracking phase,
it uses control allocation to distribute the control effort among all effectors.

Enhancing Navigation Accuracy through Cooperative Satellite Networks

Falk Ramin¹, Vincenzo Messina¹, Alessandro Golkar¹

¹ Technical University of Munich, Ottobrunn, Germany

Cooperative satellite networks have the potential to enhance navigation accuracy by
optimizing constellation design reducing Geometric Dilution of Precision (GDOP). This study
analyzes how satellite architecture parameters and receiver position influence GDOP, through
simulations with varying numbers of satellites, orbital planes, altitudes, and inclinations. Results
show that high-altitude constellations outperform lower-altitude setups in terms of GDOP,
even with fewer satellites. Increasing the satellite number improves GDOP, though this effect
diminishes beyond a threshold. Receiver locations and elevation constraints also significantly
impact GDOP. These insights support the design of adaptiv

Analog Sun Sensor Array: 4 Quadrant Sensor for Missions Beyond LEO

Marius Anger¹,  Samuli Nyman¹, Anton Fetzer¹, Jaan Praks¹

¹ Aalto University, School of Electrical Engineering, Espoo, Finland

The Foresail-2 mission demands an enhanced radiation-tolerant sun sensor to
withstand the high-radiation environment encountered in its Geostationary Transfer Orbit
(GTO). The Analog Sun Sensor Array (ASSA) is developed to fulfill this requirement, providing
attitude determination with an accuracy better than 1°. Traditional analog sun sensors, reliant
on position-sensitive diodes (PSDs), encounter challenges such as distinguishing Albedo and
celestial bodies like the Moon from the Sun, resulting in an in-orbit accuracy limitation of
approximately 5°.
ASSA utilizes four individual PSDs, each housed in a separate chamber equipped with its own
pinhole to expand the field of view, thereby overcoming previous limitations. This design has
built in triple hot redundancy. By using a STM32 controller and sufficient shielding the sensor
can be used in high radiation environments.

Distributed control for output consensus of multi-satellite systems

M. Araújo¹, P. Oliveira¹

¹ Instituto de Engenharia Mecânica - IDMEC, Lisboa, Portugal

In this paper, a non-linear output feedback control strategy is employed to design
a distributed formation controller for a constellation of satellite vehicles, in order to achieve a
coordinated action on Earth observation. The formation controller uses notions of graph algebra
and consensus theory. A stable non-linear control law is proposed to ensure consensus on a
function of the states, while actuating in the second derivative of the states, using backstepping
techniques. The control law is further adapted to the satellite’s dynamics, described through
Euler angles. Satellites with different orbits

Deep reinforcement learning-based spacecraft attitude control with pointing keep-out constraint

Juntang Yang¹, Mohamed Khalil Ben-Larbi¹

¹ University of Würzburg, Würzburg, Germany

This paper implements deep reinforcement learning (DRL) for spacecraft reorientation
control with a single pointing keep-out zone. The Soft Actor-Critic (SAC) algorithm is
adopted to handle continuous state and action space. A new state representation is designed
to explicitly include a compact representation of the attitude constraint zone. The reward
function is formulated to achieve the control objective while enforcing the attitude constraint. A
curriculum learning approach is used for the agent training. Simulation results demonstrate the
effectiveness of the proposed DRL-based method for spacecraft pointing-constrained attitude
control.

Relative Orbital Element Based Model Predictive Control for Formation Flying

R. Moen¹, W. Jordaan¹

¹ Stellenbosch University, Western Cape, South Africa

This paper presents a novel hyperparameter tuning strategy for a decentralized
Model Predictive Control (MPC) framework based on the quasi-nonsingular Relative Orbital
Elements (ROE) for satellite formation flying. We present the MPC architecture and the simulation
framework used for validation. Our key contribution is a crash-aware Bayesian optimization
algorithm that systematically tunes the MPC horizons and control weights to minimize relativeposition
RMS error across different initial conditions. Simulations incorporating the Earth’s J2
perturbation and a range of initial along-track separations evaluate the controller’s ability to
converge to specified relative distances and to station-keep. The results show that the controller’s
hyperparameters are strongly influenced by the initial conditions, and that the controller offers
a robust solution for autonomous satellite formation flying given well tuned hyperparameters.

Beacon-Enhanced Attitude Control using Optical Communication Terminals: Design and Validation in the QUBE Mission

Lisa Elsner¹, Johannes Dauner¹, Benedikt Schmidt¹, Timon Petermann¹, Malavika Unnikrishnan¹, René Rüddenklau²,  Klaus Schilling¹

¹ Center of Telematics (ZfT), Wuerzburg, Germany

² German Aerospace Center (DLR), Wessling, Germany

Achieving sub-degree pointing accuracy is essential for optical satellite communication.
To ensure accuracy, the QUBE mission demonstrates a novel two-stage attitude
control system, combining absolute pointing with ultra-fine tracking using a laser beacon
signal. While we demonstrated the absolute control with successful link establishment, the
beacon-tracking concept has undergone ground-based testing, and in-flight data confirm stable
incident angles under operating conditions. This sets the stage for future in-orbit validation. Our
analysis indicates that beacon-based tracking can improve the accuracy of relative alignment

Optimal Multi-Debris Mission Planning in LEO: A Deep Reinforcement Learning Approach with Co-Elliptic Transfers and Refueling

Agni Bandyopadhyay¹, Günther Waxenegger-Wilfing¹

¹ Department of Computer Science, Julius-Maximilians-Universität Würzburg, Germany

This paper addresses the challenge of multi-target active debris removal (ADR)
in Low Earth Orbit (LEO) by introducing a unified co-elliptic maneuver framework that
combines Hohmann transfers, safety ellipse proximity operations, and explicit refueling logic.
We benchmark three distinct planning algorithms—Greedy heuristic, Monte Carlo Tree Search
(MCTS), and deep reinforcement learning (RL) using Masked Proximal Policy Optimization
(PPO)—within a realistic orbital simulation environment featuring randomized debris fields,
keep-out zones, and ΔV constraints. Experimental results over 100 test scenarios demonstrate
that Masked PPO achieves superior mission efficiency and computational performance, visiting
up to twice as many debris as Greedy and significantly outperforming MCTS in runtime. These
findings underscore the promise of modern RL methods for scalable, safe, and resource-efficient
space mission planning, paving the way for future advancements in ADR autonomy.

Autonomous LEO-PNT System and Impact of Isoflux Navigation Antenna on Constellation

Mayank¹, Ville Lundén¹, Fabricio S. Prol², Jaan Praks¹

¹ Aalto University, Espoo, Finland

² Department of Navigation and Positioning, Finnish Geospatial Research Institute (FGI), National Land Survey of Finland (NLS), Kirkkonummi, Finland

This work proposes an autonomous Low Earth Orbit (LEO) satellite-based positioning,
navigation, and timing (PNT) system design independent of traditional GNSS infrastructure.
The system features a compact navigation payload with redundant atomic clocks,
a software-defined radio (SDR) for backhaul communications, and an isoflux-pattern antenna
for uniform ground coverage and enhanced signal robustness. The results show that increasing
antenna field-of-view (FoV) from 80◦ to 120◦ at 800km altitude reduces the constellation size
by a factor of five while maintaining four-fold global coverage. These findings suggest that
optimized antenna and payload designs can enable cost-effective and resilient autonomous LEOPNT
capabilities.

Relative Navigation for Uncooperative Cislunar Rendezvous using Body-chaser Dynamics

F. Pilone¹, G. Romagnoli¹, L. Pollini¹, G. Bucchioni¹

Department of Information Engineering, University of Pisa, Pisa, Italy

This work presents a 6-DOF relative navigation filter architecture for autonomous
rendezvous in cislunar space with an unknown and uncooperative target. The key innovation
lies in modeling all dynamics and measurements in the chaser’s body-fixed frame, enabling fullstate
estimation without requiring any knowledge of the target. The filter combines an Extended
Kalman Filter (EKF) for translation and a Multiplicative EKF (MEKF) for attitude, integrating
heterogeneous sensor data across different rendezvous phases. Despite operating under strong
non-linearities, environmental perturbations, and sensor transitions, the filters ensure accurate
and continuous estimation, supporting closed-loop control throughout the entire maneuver.

Precision and Scalability: Optimizing Attitude Control Testing for Reliable Multi-Satellite Systems

Timon Petermann¹, Vijay Nagalingesh², Tom Geiger¹, Lisa Elsner¹, Oliver Ruf², Klaus Schilling¹

¹ Zentrum für Telematik (ZfT), Würzburg, Germany

² Smart Small Satellite Systems GmbH (S4), Würzburg, Germany

Ground-based testing is essential for verifying nanosatellite attitude determination
and control systems (ADCSs). To ensure reliability in satellite constellations despite the higher
number of satellites, efficient and scalable test strategies and environments need to be developed.
Conventional testbeds present challenges - air-bearing systems restrict test scenarios, while
turntables exclude actuators. We propose a hybrid hardware-in-the-loop (HiL) test strategy
that separately evaluates estimation and actuation, leveraging turntables for sensor validation
and air-bearing platforms for actuator testing. Through mission case studies, we demonstrate
the effectiveness of this approach and indicate

CBBA-based Decentralized Task Allocation Framework for Multiple Observation Satellites

Kisung Lee¹, Sung Jun Kim¹, Minchae Kim¹, Han-Lim Choi¹

¹ Korea Advanced Institute of Science and Technology

In this study, we propose a decentralized task allocation algorithm for Earth observation
missions utilizing a Low Earth Orbit (LEO) Synthetic Aperture Radar (SAR) satellite
constellation. By employing the Consensus-Based Bundle Algorithm (CBBA), each satellite
autonomously evaluates observation tasks based on priority, requested observation times, and
imaging angles. Through iterative consensus and bundle adjustments, the proposed method
ensures conflict-free task assignments without requiring centralized coordination. Simulation
results demonstrate that the decentralized framework achieves high task coverage, maximizing
task allocation per satellite and effectively meeting observation requests. The proposed approach
provides enhanced

An evaluation of Sample Average Approximation applied to the design of impulsive thrust space collision avoidance maneuvers

Denis Arzelier¹, Fabrizio Dabbene², Mioara Joldes¹, Martina Mammarella², Matthieu Masson¹, Pema Mercereau-Boland¹

¹ LAAS-CNRS, Université de Toulouse 31400 Toulouse, France

² CNR-IEIIT, c/o Politecnico di Torino, Torino, Italy

This paper investigates how Sample Average Approximation (SAA) techniques can be applied to
chance-constrained optimization problems defined for collision avoidance maneuvers design between
an active satellite and a passive space debris. The objective is to compute impulsive evasive maneuvers
that minimize the fuel consumption of the active asset and simultaneously maintaining the collision
probability below a given threshold. A particular SAA algorithm is then proposed and compared against
a direct optimization algorithm using both synthetic and real conjunction data.

Control Requirements for Robust Beamforming in Multi-Satellite Systems

Diego Tuzi¹, Thomas Delamotte¹, Andreas Knopp¹

¹ Chair of Signal Processing, University of the Bundeswehr Munich, Neubiberg, Germany

This work investigates the impact of position and attitude perturbations on the
beamforming performance of multi-satellite systems. The system under analysis is a formation
of small satellites equipped with direct radiating arrays that synthesise a large virtual antenna
aperture. The results show that performance is highly sensitive to the considered perturbations.
However, by incorporating position and attitude information into the beamforming process,
nominal performance can be effectively restored. These findings support the development of
control-aware beamforming strategies that tightly integrate the attitude and orbit control system
with signal processing to enable robust beamforming and autonomous coordination.
Keywords: multi-satellite systems, beamforming, attitude and orbit control, phase alignment

A Dual Quaternion based RRT* Path Planning Approach for Satellite Rendezvous and Docking

A. Stankovic¹, M.K. Ben-Larbi²,  W.H. Müller¹

¹ TU Berlin, Chair of Continuum Mechanics and Consitutive Theory, Berlin, Germany

² University of Würzburg, Chair of Space Informatics and Satellite Systems, Würzburg, Germany

This paper proposes a sampling-based motion planner that employs a dual quaternion
representation to generate smooth, collision-free six-degree-of-freedom pose trajectories for
satellite rendezvous and docking under keep-out zone constraints. The proposed planner integrates
the dual quaternion algebra directly into an RRT* framework, thereby enabling natural
screw motion interpolation in SE(3). The dual quaternion-based RRT* has been implemented
in Python and demonstrated on a representative multi-obstacle scenario. A comparison with
a standard RRT* using separate translation and quaternion steering highlights the enhanced
pose continuity and obstacle avoidance of the proposed method. The present approach is purely
kinematic in nature and does not take into account relative orbital dynamics. Consequently, the
resulting path provides a preliminary estimate for a subsequent optimisation-based trajectory
planner, which will refine the motion with dynamic constraints for the purpose of practical
satellite rendezvous and docking missions.

Trajectory Optimization for Multi-Agent 6-DOF On-Orbit Inspection Missions

Chala Adane Deresa¹, Dong-Woo Han¹, Han-Lim Choi¹

¹ Aerospace Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea

Reliable inspection of resident space objects requires trajectories that maximize
sensing quality while respecting the stringent propellant and safety constraints of small
inspector satellites. While prior work has explored trajectory planning for such missions,
most approaches optimize the vehicle’s translational path first and treat attitude control as
a secondary consideration. This decoupling can be suboptimal when sensor pointing strongly
influences the quality of information collected. We formulate multi-spacecraft inspection as
a multiphase six-degree-of-freedom (6-DOF) optimal control problem that simultaneously
optimizes each inspector’s translation and attitude trajectories. A differentiable visibility
metric—incorporating surface-normal alignment, field-of-view constraints, range attenuation,
and motion penalties—serves as a proxy for observation quality within the optimizer. Numerical
simulations with up to three inspectors and up to 50 inspection points demonstrate that
the algorithm produces coordinated, fuel-efficient, information-rich trajectories while ensuring
collision avoidance.

Consensus Control in Time varying Nonlinear Fractional-Order Multi-Agent Systems: LMI-Driven Stability Analysis and DoS Attack
Detection

Mohammad Fiuzy¹, Stefan Rass¹

¹ LIT Secure and Correct Systems Laboratory, Johannes Kepler University Linz, Linz, Austria

This paper presents a novel consensus control framework for nonlinear fractional-order multi-agent systems (MAS)
operating under Denial-of-Service (DoS) attacks. The proposed approach addresses the challenges posed by time-varying
uncertainties and adversarial disruptions in communication networks. A distributed control strategy is developed for agents
with Caputo-type fractional-order dynamics, incorporating memory effects and bounded uncertainties. Stability is analyzed
using fractional-order Lyapunov methods and a generalized Gronwall–Bellman lemma, leading to sufficient conditions for
asymptotic stability under DoS attacks. Furthermore, a controller synthesis based on Linear Matrix Inequalities (LMI) is
proposed, enabling robust consensus and supporting a mechanism for detecting DoS attacks within the framework of the
algorithm presented. Simulation results indicate the proposed method's effectiveness in achieving resilient consensus, even
under extreme attack conditions. The findings highlight the robustness and scalability of the framework, making it suitable
for cooperative applications.

Modelling and Simulation of GNSS Observables for Spacecraft Navigation

A. Michelazzi¹, G. Gaias¹, C. Colombo¹

¹ Department of Aerospace Science and Technology, Politecnico di Milano, Milan, Italy

GNSS-based navigation plays a central role in space applications, supporting both
absolute and relative navigation. New mission concepts are targeting tight formations with
baselines as short as 5–13 m, where accurate characterisation of GNSS observables becomes
critical during early algorithm development.
The GNSS Environment and Measurements Simulator (GEMS) is being developed at Politecnico
di Milano and is meant to support the development and early prototyping of (relative) navigation
algorithms. It features a modular architecture and simulates raw GNSS measurements received
onboard. GEMS models key error sources, such as clock biases, ionospheric delay, and thermal
noise, and integrates real data from the International GNSS Service (IGS), including precise
products and ionospheric maps.
Validation against flight data from the Sentinel-3 and Sentinel-6 missions shows that GEMS
achieves simulation errors at the metre level, while successfully reproducing the temporal
behaviour of GNSS observables. These results demonstrate that GEMS provides a reliable and
cost-effective platform for early-stage algorithm development and Model-in-the-Loop testing,
bridging the gap between simplistic error models and high-fidelity hardware simulators.

Constrained Formation Control Framework for Spacecraft Proximity Formation Flight

D. Ruggiero¹, P. Bertuccio¹, E. Capello¹

¹ Politecnico di Torino, Torino, Italy

This paper presents an analytical framework for designing Artificial Potential Field (APF)
gains for spacecraft formation control within the Circular Relative Orbit framework. While APF
methods are effective for formation shaping, they often overlook system dynamics and constraints,
risking instability. The proposed method ensures Lyapunov stability through a systematic gain design
and the definition of an operational bound. Stability is verified using Structured Singular Value
μ-analysis. Numerical simulations confirm the robustness and scalability of the approach, supporting

Decentralized Collision-Free Satellite Formation Reconfiguration with Control Barrier Functions

Jihyeok Kim¹, Hancheol Cho¹

¹ Yonsei University, Seoul, Korea

This paper develops a Control Barrier Function (CBF)-based safety filter, extended
from safety barrier certificates originally designed for simple double integrator systems, to
achieve collision-free reconfiguration of multiple satellites in formation. The proposed decentralized
framework integrates observer-based relative state estimation with CBF-based safety
filtering, enabling each satellite to assess potential collisions with neighboring satellites based
on relative position and velocity measurements. Safe control inputs are computed in real time
by solving a decentralized quadratic program, which minimally modifies the nominal control to
enforce safety constraints while relying solely on local sensor information. A numerical simulation
of eight satellites initially placed at the vertices of a cube and reconfigured by swapping positions
with their diagonal counterparts validates the effectiveness of the proposed approach.

Forecasting Thermospheric Density with Transformers for Multi-Satellite Orbit Management

Cedric Bös¹, Alessandro Bortotto¹, Mohamed Khalil Ben-Larbi¹

¹ Julius-Maximilians-Universität Würzburg, Chair of Space Computer Science and Satellite Systems, Am Hubland, Würzburg, Germany

Accurate thermospheric density prediction is crucial for reliable satellite operations
in Low Earth Orbits, especially at high solar and geomagnetic activity. Physics-based models
such as TIE-GCM offer high fidelity but are computationally expensive, while empirical models
like NRLMSIS are efficient yet lack predictive power. This work presents a transformer-based
model that forecasts densities up to three days ahead and is intended as a drop-in replacement
for an empirical baseline. Unlike recent approaches, it avoids spatial reduction and complex
input pipelines, operating directly on a compact input set. Validated on real-world data,

Sector-Bounded Control of Small Satellite Formations in Low Earth Orbits

Florian kempf¹, Julian Scharnagl², Lakshminarasimhan Srinivasan³, Dušan M. Stipanović⁴, Klaus Schilling¹

¹ Center for Telematics, Würzburg, Germany 

² Berlin, Germany 

³ Computer Science Dept., University of Würzburg, Germany 

⁴ Coordinated Science Laboratory and Industrial and Enterprise Systems Engineering, University of Illinois Urbana-Champaign, Urbana, USA

This paper presents a sector-bounded robust control approach for small satellite
formations in Low Earth Orbit. Using the Hill-Clohessy-Wiltshire model augmented with sector
bounds for nonlinearities and disturbances, we synthesize computationally ecient constantgain
controllers via linear matrix inequalities. The method guarantees asymptotic stability
while maintaining low computational complexity suitable for resource-constrained satellites.
Simulation results demonstrate successful formation control with minimal thrust requirements.

LEO-GYM: A Reinforcement Learning Library for Satellite Control in LEO

Nektarios Aristeidis Tafanidis¹, Avijit Banerjee¹, George Nikolakopoulos¹

¹ Robotics and AI group, Luleå University of Technology

Motivated by recent advances in Reinforcement Learning (RL) and the lack of open-source
tools for training and benchmarking satellite guidance and control, we introduce LEO-GYM:
a lightweight Python library for formulating RL problems for satellites in Low Earth Orbit
(LEO). The framework decomposes problems into three classes, the low-level dynamics, the
training environment and a satellite object that bridges them. LEO-GYM enables the creation
of custom scenarios without imposing rigid class hierarchies. We present the architecture, key
components, and an illustrative orbit-correction task modeled as a semi-Markov decision process.
LEO-GYM is released as open-source to support and foster reproducible research in autonomous
space operations.