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Eng. Proc., 2026, ENC 2025

European Navigation Conference 2025

Wrocław, Poland | 21–23 May 2025

Volume Editor:
Tomasz Hadaś , Institute of Geodesy and Geoinformatics, Wrocław University of Environmental and Life Sciences, Wrocław, Poland

Number of Papers: 53
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Cover Story (view full-size image): The European Navigation Conference 2025 (ENC 2025) was held from 21 to 23 May 2025 at the Centennial Hall Complex in Wrocław, Poland. The conference was organized by the Polish Navigation Forum as [...] Read more.
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9 pages, 1669 KB  
Proceeding Paper
Performance Evaluation of GNSS Message Structures: Insights for Future Design
by Jae Hee Noh, Jae Min Ahn and Jong Yeon Choi
Eng. Proc. 2026, 126(1), 1; https://doi.org/10.3390/engproc2026126001 - 5 Feb 2026
Viewed by 564
Abstract
As a fundamental component of GNSS signals, messages act as a critical medium for transmitting information required for PNT, serving the needs of both service providers and users. Over the years, message structures for GNSS signals have evolved from fixed formats to pseudo-packetized [...] Read more.
As a fundamental component of GNSS signals, messages act as a critical medium for transmitting information required for PNT, serving the needs of both service providers and users. Over the years, message structures for GNSS signals have evolved from fixed formats to pseudo-packetized and mixed formats. This evolution has facilitated the integration of supplementary data and has driven further research to incorporate new types of information. These developments have highlighted the necessity of flexible and transmission-efficient message structures. In this paper, we propose a set of performance metrics designed for the comprehensive evaluation of GNSS message structures. Using these metrics, we analyze the performance of existing message formats. From the results, it is observed that optimizing message formats based on the purpose and characteristics of the transmitted information could achieve flexibility and transmission efficiency. Based on these findings, we propose a novel approach to designing message structures that address future requirements. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 1913 KB  
Proceeding Paper
Deep Learning Assisted Composite Clock: Robust Timescale for GNSS Through Neural Network
by Gaëtan Fayon, Alexander Mudrak, Hugo Sobreira and Artemio Castillo
Eng. Proc. 2026, 126(1), 2; https://doi.org/10.3390/engproc2026126002 - 5 Feb 2026
Viewed by 346
Abstract
This study introduces the Deep Learning Assisted Composite Clock (DLACC), aiming to improve the robustness of the GNSS timescale. If traditional Kalman filter-based composite clocks are today used in systems like GPS and EGNOS, the non-linear, non-Gaussian, and non-stationary behavior of atomic clocks [...] Read more.
This study introduces the Deep Learning Assisted Composite Clock (DLACC), aiming to improve the robustness of the GNSS timescale. If traditional Kalman filter-based composite clocks are today used in systems like GPS and EGNOS, the non-linear, non-Gaussian, and non-stationary behavior of atomic clocks can impact the performance of such model-based filtering. DLACC, built from the KalmanNet approach, proposes to enhance Kalman filters by computing its gain through a neural network to better model clock dynamics and manage ensemble clock reconfigurations. In particular, this study evaluates this method’s performance against conventional filters, demonstrating its potential for more resilient and adaptive GNSS timescales. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 2910 KB  
Proceeding Paper
Experimentation of an Integrated Vision-Aided Inertial Navigation System with Orthophoto Matching on a Fixed-Wing UAV
by Baheerathan Sivalingam and Ove Kent Hagen
Eng. Proc. 2026, 126(1), 3; https://doi.org/10.3390/engproc2026126003 - 5 Feb 2026
Viewed by 397
Abstract
This paper presents the work on integrating our Vision-Aided Inertial Navigation System (VaINS) with orthophoto matching to increase robustness to GNSS failure. Normalized cross-correlation is used to match onboard camera images with geo-referenced aerial imagery. Image sequences captured at a nadir angle by [...] Read more.
This paper presents the work on integrating our Vision-Aided Inertial Navigation System (VaINS) with orthophoto matching to increase robustness to GNSS failure. Normalized cross-correlation is used to match onboard camera images with geo-referenced aerial imagery. Image sequences captured at a nadir angle by VaINS on a fixed-wing UAV are used in this experiment. The integrated navigation results are compared to both a smoothed GNSS-aided reference solution and the standalone VaINS solution during simulated GNSS-denied intervals. The results demonstrate that the integrated approach significantly outperforms the VaINS-only method. This is a preliminary investigation within ongoing work in orthophoto matching. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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8 pages, 1974 KB  
Proceeding Paper
Monitoring Radio Frequency Interference Affecting GNSS Using Android Smartphones
by Javier Tegedor, Ciro Gioia, Marco Barbero, Stefano Luzardi and Gianluca Folloni
Eng. Proc. 2026, 126(1), 4; https://doi.org/10.3390/engproc2026126004 - 5 Feb 2026
Viewed by 924
Abstract
Global Navigation Satellite Systems (GNSSs) are exploited in a wide range of applications, and their reliability and accuracy are more critical than ever. Weak GNSS signals are extremely susceptible to intentional or unintentional interference. The Joint Research Centre has explored the potential of [...] Read more.
Global Navigation Satellite Systems (GNSSs) are exploited in a wide range of applications, and their reliability and accuracy are more critical than ever. Weak GNSS signals are extremely susceptible to intentional or unintentional interference. The Joint Research Centre has explored the potential of leveraging the ubiquitous presence of Android smartphones for interference monitoring. Automatic Gain Control (AGC) measurements provided by the Android GNSS API are used for this purpose. A proof-of-concept, including an App to collect data and a back-end server for processing, has been developed and tested. The proposed approach demonstrates the potential to detect both intentional and unintentional interference. However, the approach has limitations, such as small AGC variations that cannot always be linked to GNSS interference and significant differences among smartphone models, which need to be considered for effective crowdsourcing. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 1356 KB  
Proceeding Paper
Assessing the Quality of Products and Latest Performance of Galileo HAS (High Accuracy Service) Using Real-Time Data
by Stepan Savchuk, Vladyslav Kerker, Janusz Ćwiklak and Piotr Miduch
Eng. Proc. 2026, 126(1), 5; https://doi.org/10.3390/engproc2026126005 - 5 Feb 2026
Viewed by 961
Abstract
The Galileo High Accuracy Service (HAS) offers free, real-time precise point positioning (PPP) corrections via Galileo (E6-B) and internet, supporting Galileo (E1, E5a, E5b, E6) and GPS (L1, L5) signals. As of Service Level 1, HAS provides SSR orbit, clock corrections, and biases, [...] Read more.
The Galileo High Accuracy Service (HAS) offers free, real-time precise point positioning (PPP) corrections via Galileo (E6-B) and internet, supporting Galileo (E1, E5a, E5b, E6) and GPS (L1, L5) signals. As of Service Level 1, HAS provides SSR orbit, clock corrections, and biases, achieving decimeter-level accuracy (20 cm horizontal, 40 cm vertical) within 300 s (95th percntile), per the HAS ICD. This study compares HAS products with other analysis centers, verifying declared accuracy. Using a Septentrio Mosaic X5 GNSS receiver, real-time HAS data was collected over three weeks, verified against CODE products, and assessed for PPP performance under various scenarios to evaluate HAS reliability for high-accuracy positioning. The analysis has shown that HAS products provide superior accuracy for Galileo (9.6 cm URE) over GPS (14.0 cm URE) and enable decimeter-level positioning convergence within 3–5 min, although significant outliers were detected in the GPS clock corrections. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 1444 KB  
Proceeding Paper
GRIPP: An Open-Source and Portable Software-Defined Radio-Oriented GNSS/SBAS Receiver
by Gaëtan Fayon, Nicolas Castel, Hugo Sobreira, Ciprian-Vladut Circu, Noori Bni Lam, Marnix Meersman, Leia Nummisalo, Ruediger Matthias Weiler, Jörg Hahn, Stefan Wallner and Nityaporn Sirikan
Eng. Proc. 2026, 126(1), 6; https://doi.org/10.3390/engproc2026126006 - 6 Feb 2026
Cited by 1 | Viewed by 722
Abstract
This paper introduces the GRIPP (GNSS/SBAS Receiver, Independent and Portable PVT) system, an open-source SDR oriented GNSS/SBAS receiver. Composed of a Pocket SDR FE device, an L-band antenna and a computer, this system aims to ease the deployment and test of future GNSS [...] Read more.
This paper introduces the GRIPP (GNSS/SBAS Receiver, Independent and Portable PVT) system, an open-source SDR oriented GNSS/SBAS receiver. Composed of a Pocket SDR FE device, an L-band antenna and a computer, this system aims to ease the deployment and test of future GNSS and SBAS evolutions, providing a fully documented and customizable receiver. Acting like a generic navigation toolbox, the main idea is to be able to quickly adapt it for research and development purposes, introducing new filtering methods or PVT algorithms. Besides these engineering applications, the goal is also to use it for educational purposes to introduce GNSS and SBAS to the general audience. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 1096 KB  
Proceeding Paper
A Dynamic Approach for Operational Efficiency Improvement Using Adaptive Particle Swarm Optimization
by Hari Sundar Mahadevan and Ashwarya Kumar
Eng. Proc. 2026, 126(1), 7; https://doi.org/10.3390/engproc2026126007 - 6 Feb 2026
Viewed by 332
Abstract
The maritime industry is experiencing significant growth due to globalized trade, but this expansion has led to increasing environmental concerns. Studies project that shipping emissions could reach 90–130% of 2008 levels by 2050 without intervention potentially contributing up to 17% of global CO [...] Read more.
The maritime industry is experiencing significant growth due to globalized trade, but this expansion has led to increasing environmental concerns. Studies project that shipping emissions could reach 90–130% of 2008 levels by 2050 without intervention potentially contributing up to 17% of global CO2 emissions by 2050, thereby posing a major environmental challenge. Stringent environmental regulations from international organizations and government agencies necessitate the maritime industry to find effective solutions to reduce its greenhouse gas (GHG) emissions and improve energy efficiency. This research proposes a methodology for dynamically calculating optimal ship speed to enhance energy efficiency and reduce GHG emissions. By leveraging real-time environmental data (e.g., weather forecasts, sea state information) and operational parameters (e.g., ship characteristics, cargo load), the study utilizes an Adaptive Particle Swarm Optimization based on Velocity Information (APSO-VI) to predict optimal speed over ground (SOG) in real time. The study utilizes the Energy Efficiency Operational Index (EEOI) as a performance metric. EEOI is a widely employed measure in the maritime industry that quantifies the grams of CO2 emitted per tonne-nautical mile (g CO2/t nm) of transport work. The effectiveness of the proposed dynamic optimization model (APSO-VI) is assessed by comparing its performance with constant velocity models through extensive simulations, showing a 5–12% reduction in EEOI with the optimized speed model. The results demonstrate significant reductions in fuel consumption and emissions, supporting the adoption of such technologies for a more sustainable maritime industry. Future research may explore integrating machine learning techniques and advanced weather forecasting models for even more robust optimization strategies. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 925 KB  
Proceeding Paper
New Approach for Jamming and Spoofing Detection Mechanisms for High Accuracy Solutions
by María Crespo, Adrián Chamorro, Miguel Ángel Azanza and Ana González
Eng. Proc. 2026, 126(1), 8; https://doi.org/10.3390/engproc2026126008 - 6 Feb 2026
Viewed by 782
Abstract
It is well-known that GNSS high accuracy solutions are increasingly vulnerable to jamming and spoofing attacks, posing significant challenges to their reliability, security, and accuracy. In the past years, GNSS communities have witnessed an increase in the frequency and sophistication of these attacks, [...] Read more.
It is well-known that GNSS high accuracy solutions are increasingly vulnerable to jamming and spoofing attacks, posing significant challenges to their reliability, security, and accuracy. In the past years, GNSS communities have witnessed an increase in the frequency and sophistication of these attacks, driven, among other factors, by the widespread availability of low-cost, off-the-shelf equipment capable of denying or even totally misleading GNSS-based positioning systems. On the one hand, jamming attacks aim at inhibiting signal reception by introducing high-power noise or interference, leading to degraded performance or complete failure in determining position. Jamming detection mechanisms need to be traced to GNSS receiver mitigation measures at signal processing level to analyze the radio frequency (RF) environment or receiver behavior. Signal-to-noise ratio (SNR) monitoring, power spectrum analysis, and signal power monitoring are commonly used to detect anomalies in signal characteristics. Jamming is often indicated with the presence of a combination of one or more dedicated indicators, opening space to characterize different levels of jamming attack allowing to optimize a response at user level. On the other hand, detecting spoofing attacks requires different advanced techniques to identify anomalies in satellite signals, receiver behavior, or consistency of computed position data. Indicators regarding internal consistency checks, as well as unexpected evolutions of GNSS signals, are typically suspicious behaviors to be analyzed as possible attacks. Additionally, ensuring trust in the received navigation information by including cryptographic authentication mechanisms is key to quickly detecting some kinds of spoofing. This paper presents the latest enhancements on jamming and spoofing detection and mitigation mechanisms for GMV GSharp® high accuracy and safe positioning solution. This new method, based on fuzzy logic systems, allows us to distinguish between different levels of attack and adapt the reactions to reduce the impact on the final user as much as possible. Additionally, test results obtained from real GNSS attacks datasets will be shown. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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11 pages, 805 KB  
Proceeding Paper
Inter-Satellite Link Network Real-Time Ring Dissemination Performance and Robustness
by Enrico Edoardo Zini, Christina Wagner, Pasquale Christian Neto and Andrea Morelli
Eng. Proc. 2026, 126(1), 9; https://doi.org/10.3390/engproc2026126009 - 11 Feb 2026
Viewed by 476
Abstract
Inter-Satellite Link (ISL) technology in GNSS constellations improves Monitoring and Control (M&C), data dissemination, and accuracy of ODTS products. ISL-enabled networks can distribute data via Single (SH) or Multiple Hop (MH) routing logics: this work analyzes the performance and robustness of a MH [...] Read more.
Inter-Satellite Link (ISL) technology in GNSS constellations improves Monitoring and Control (M&C), data dissemination, and accuracy of ODTS products. ISL-enabled networks can distribute data via Single (SH) or Multiple Hop (MH) routing logics: this work analyzes the performance and robustness of a MH RTR (Real-Time Ring) network both in nominal conditions and in the presence of ISL payloads failures (e.g., due to aging). The KPIs are assessed under no ground intervention upon failure detection and with ground-initiated mitigation actions like contact replanning and satellite isolation. Performance is measured by data dissemination time from generation to target satellites. Recommendations for improving network strategies and future work are discussed. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 2590 KB  
Proceeding Paper
On the Context-Aware GNSS Navigation: Test of a k-Nearest Neighbors Classifier in Different Environments
by Giovanni Cappello, Antonio Angrisano, Ciro Gioia, Antonio Maratea and Salvatore Gaglione
Eng. Proc. 2026, 126(1), 10; https://doi.org/10.3390/engproc2026126010 - 11 Feb 2026
Viewed by 419
Abstract
GNSS navigation can be challenging in urban environments, especially when low-cost devices are adopted. Among the possible solutions, in more recent years, approaches based on Machine Learning became popular. In this work, features based on geometry, satellite visibility and carrier-to-noise ratio are used [...] Read more.
GNSS navigation can be challenging in urban environments, especially when low-cost devices are adopted. Among the possible solutions, in more recent years, approaches based on Machine Learning became popular. In this work, features based on geometry, satellite visibility and carrier-to-noise ratio are used in combination with k-Nearest Neighbors classifier to distinguish between open-sky and obstructed environments. The purpose of this research is to develop a reliable context classifier, to evaluate its recognition capabilities in static and dynamic environments and to assess its applicability in real-time positioning. Several performance metrics have been used, i.e., accuracy, precision, recall, F1-score, and multiple tests have been carried out to demonstrate the reliability of such algorithm with validation data. More than 98% of classification accuracy for the static tests has been obtained in average, evidencing the detection capabilities of such an algorithm. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 629 KB  
Proceeding Paper
Comparative Analysis of Factor Graph Models for Carrier Phase-Based Precision Navigation
by Tibor Dome, Theodore Russell, Miguel Ortiz Rejon, Yuheng Zheng, Elisa Benedetti, Teng Li, Mengwei Sun and Ivan Petrunin
Eng. Proc. 2026, 126(1), 11; https://doi.org/10.3390/engproc2026126011 - 13 Feb 2026
Viewed by 692
Abstract
Factor graph optimization (FGO) has emerged as a powerful alternative to Kalman filtering for high-precision GNSS positioning, particularly under challenging conditions. Its modular structure allows for the seamless integration of motion constraints, ambiguity modeling, and multi-sensor data across diverse platforms and environments. This [...] Read more.
Factor graph optimization (FGO) has emerged as a powerful alternative to Kalman filtering for high-precision GNSS positioning, particularly under challenging conditions. Its modular structure allows for the seamless integration of motion constraints, ambiguity modeling, and multi-sensor data across diverse platforms and environments. This study reviews recent FGO architectures for high-precision GNSS methodologies (PPP, RTK), comparing ambiguity management strategies, measurement factor designs, and robust optimization techniques. We compare strategies for modeling ambiguities within the graph and evaluate how they interact with measurement factor design, cycle slip detection, and integer ambiguity resolution (IAR). Trade-offs in ambiguity management and optimization techniques are discussed to guide future design choices. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 13105 KB  
Proceeding Paper
Experimental Testbed and Measurement Campaign for Multi-Constellation LEO Positioning
by Marc Fernández-Temprado, Antoni Reus-Bergas, Gonzalo Seco-Granados and José A. López-Salcedo
Eng. Proc. 2026, 126(1), 12; https://doi.org/10.3390/engproc2026126012 - 14 Feb 2026
Viewed by 687
Abstract
The proliferation of Low Earth Orbit (LEO) satellite constellations, driven by the NewSpace economy and reduced launch costs, has opened new opportunities for positioning, navigation, and timing (PNT) applications. Compared to traditional GNSS systems operating in Medium Earth Orbit, LEO satellites offer several [...] Read more.
The proliferation of Low Earth Orbit (LEO) satellite constellations, driven by the NewSpace economy and reduced launch costs, has opened new opportunities for positioning, navigation, and timing (PNT) applications. Compared to traditional GNSS systems operating in Medium Earth Orbit, LEO satellites offer several advantages: higher received signal power, better satellite geometry and visibility in urban environments, and greater Doppler dynamics—enabling approaches such as single-satellite and Doppler-based positioning. Although dedicated LEO-PNT constellations are still under development, existing commercial LEO satellites can already be leveraged for experimental positioning applications. This paper presents a portable, multi-constellation testbed built using commercial off-the-shelf (COTS) hardware and software-defined radio (SDR) technologies. The platform enables the synchronous acquisition and processing of LEO signals from Orbcomm, Iridium, and Starlink, allowing for the extraction of key positioning observables. A comprehensive measurement campaign is conducted across both indoor and outdoor environments to evaluate signal visibility and Doppler tracking performance. Results highlight the potential of opportunistic LEO-based positioning, particularly in challenging scenarios such as indoor environments where traditional GNSS solutions are unreliable. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 930 KB  
Proceeding Paper
Analysis of the Galileo SAR Return Link Service Using the GalileoSARlib Open-Source Library
by Aleix Galan-Figueras, Ignacio Fernandez-Hernandez, Gonzalo Seco-Granados and Sofie Pollin
Eng. Proc. 2026, 126(1), 13; https://doi.org/10.3390/engproc2026126013 - 14 Feb 2026
Viewed by 423
Abstract
The Galileo Search and Rescue (SAR) service is the contribution from the European constellation to the international Cospas–Sarsat system. This system uses a variety of space and ground infrastructure to detect and localize distress signals from beacons on the 406 MHz frequency. Satellites [...] Read more.
The Galileo Search and Rescue (SAR) service is the contribution from the European constellation to the international Cospas–Sarsat system. This system uses a variety of space and ground infrastructure to detect and localize distress signals from beacons on the 406 MHz frequency. Satellites in different orbits detect the signals coming from the Earth and transmit them back to Earth stations that route them to the appropriate government authorities. On top of the standard detection and relay service, the Galileo constellation is the first to offer a Return Link Service (RLS) that acknowledges the processing of the distress signal with a Return Link Message (RLM) back to the originating beacon. This RLM is transmitted in the SAR field of the E1 signal I/NAV message, which allocates 20 bits every 2 s page. Therefore, transmitting a short RLM (80 bits) takes four consecutive pages or eight seconds. Moreover, each RLM is transmitted in parallel from two Galileo satellites. The RLS has been active since 2020, avoiding the spotlight of the GNSS community. This paper presents an analysis of the SAR Return Link Messages extracted from more than 3 months of signal-in-space data to investigate the current bandwidth use, monitor the type of SAR usage, and detect anomalies in the service. To extract and parse the Return Link Messages, we have developed and published an open-source Python library called GalileoSARlib on GitHub, which is also detailed in the paper. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 1901 KB  
Proceeding Paper
Toward an Interpretable Multipath Error Model from GNSS Observables Through the Application of Deep Learning
by Thomas Barbero, Eustachio Roberto Matera, Bertrand Ekambi, Jeremy Chamard and Mathieu Ekambi
Eng. Proc. 2026, 126(1), 14; https://doi.org/10.3390/engproc2026126014 - 14 Feb 2026
Viewed by 416
Abstract
Multipath degradation of GNSS measurements is the main source of error in urban areas. Robust mitigation of this error source is still a challenge for standalone low-cost GNSS receivers. The complexity associated with the development of Multipath degradation models requires the use of [...] Read more.
Multipath degradation of GNSS measurements is the main source of error in urban areas. Robust mitigation of this error source is still a challenge for standalone low-cost GNSS receivers. The complexity associated with the development of Multipath degradation models requires the use of advanced methods such as Deep Learning. However, Deep Learning based mitigation methods tend to be hard to deploy due to a general lack of trust in their prediction due to their “black-box” behavior. This work tackles the notion of interpretability and generalization of multipath degradation models obtained using Auto-Encoders. We demonstrate the ability of Auto-Encoders to generate interpretable representations and to generalize to unseen situations. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 1909 KB  
Proceeding Paper
Verification of Two-Way Time Transfer Accuracy Through a Closed-Loop Topology of Inter-Satellite and Satellite-Ground Optical Links
by Manuele Dassié, Grzegorz Michalak and Gabriele Giorgi
Eng. Proc. 2026, 126(1), 15; https://doi.org/10.3390/engproc2026126015 - 14 Feb 2026
Viewed by 323
Abstract
The exploitation of Optical Inter-Satellite Links (OISLs) has the potential to provide significant benefits to GNSSs, offering clock synchronization via highly accurate time transfer, precise ranging, robustness against jamming and spoofing, high data rates, and freedom from signal frequency regulations. As with any [...] Read more.
The exploitation of Optical Inter-Satellite Links (OISLs) has the potential to provide significant benefits to GNSSs, offering clock synchronization via highly accurate time transfer, precise ranging, robustness against jamming and spoofing, high data rates, and freedom from signal frequency regulations. As with any new technology, it is crucial to conduct in-space experiments to demonstrate the capabilities of OISLs before widespread adoption. In this work, we present preliminary analyses of an in-orbit demonstrator concept, which is being designed under the name Optical Synchronized Time And Ranging (OpSTAR). It involves two satellites in a trailing configuration, each equipped with two laser terminals. On the ground, two co-located Optical Ground Stations (OGSs) are operated. Whenever both satellites are simultaneously visible from the OGSs, an OISL and two additional Optical Satellite-to-Ground Links (OSGLs) are established, forming a closed “measurement loop” between the two satellites and the two ground stations. We present a functional model for OISL and OSGL pseudorange observables. A cross-link clock observable is formed by differencing two one-way pseudoranges, from which a relative clock offset estimate is obtained. First, we analyze how modeling errors on differential delays in Two-Way Time Transfer (TWTT)—relativistic effects, atmospheric delays, hardware delays, and satellite dynamics during the exchange—impact the estimation accuracy. Next, we study the impact of individual error contributions to the overall zero-sum chain of clock offset estimates across the closed-loop. Results show that errors due to mis-modeling of relativistic effects, satellite dynamics and clock instability are negligible, while hardware and atmospheric delays require accurate calibrations to achieve TWTT at picosecond-level accuracy. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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8 pages, 1854 KB  
Proceeding Paper
VTOL Navigation Based on Radar Altimeter and Ground RF Repeaters
by Petr Kejik, Tomas Beda, Jan Reznicek, Michal Dobes, Jan Lukas and Vibhor Bageshwar
Eng. Proc. 2026, 126(1), 16; https://doi.org/10.3390/engproc2026126016 - 19 Feb 2026
Viewed by 364
Abstract
This paper introduces an innovative radar-based navigation approach designed to address precision navigation challenges for Vertical Take-Off and Landing (VTOL) platforms. The key innovation is a unique extension of radar altimeter functionality when used with ground navigation beacons realized by Radio Frequency (RF) [...] Read more.
This paper introduces an innovative radar-based navigation approach designed to address precision navigation challenges for Vertical Take-Off and Landing (VTOL) platforms. The key innovation is a unique extension of radar altimeter functionality when used with ground navigation beacons realized by Radio Frequency (RF) repeaters. The proposed solution is intended to support helicopter and Advanced Air Mobility (AAM) autonomous operations. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 1617 KB  
Proceeding Paper
ARAIM Protection Level Calculation Method Based on Bayesian Optimization
by Sitong Liu, Xiao Liang, Peng Zhao, Pengyu Zhao, Zhongxiang Li and Chuanjun Li
Eng. Proc. 2026, 126(1), 17; https://doi.org/10.3390/engproc2026126017 - 20 Feb 2026
Viewed by 358
Abstract
In Advanced Receiver Autonomous Integrity Monitoring (ARAIM), the allocation of continuity risk influences the fault detection threshold. A higher fault detection threshold increases the probability of hazardous misleading information (HMI), thereby elevating both the integrity risk and the protection level and ultimately reducing [...] Read more.
In Advanced Receiver Autonomous Integrity Monitoring (ARAIM), the allocation of continuity risk influences the fault detection threshold. A higher fault detection threshold increases the probability of hazardous misleading information (HMI), thereby elevating both the integrity risk and the protection level and ultimately reducing ARAIM availability. While traditional ARAIM employs an equal allocation approach, this method is inefficient in practice because it fails to account for the varying continuity risk profiles of individual satellites, resulting in redundant risk distribution. This paper proposes a Bayesian Optimization-based ARAIM protection level calculation method, where the minimum Vertical Protection Level (VPL) is set as the objective function. Using the Bayesian Optimization algorithm, the continuity risks of different fault modes are reallocated, optimizing the VPL and improving the global availability of ARAIM. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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11 pages, 1220 KB  
Proceeding Paper
Enhanced GNSS Threat Detection: On-Edge Statistical Approach with Crowdsourced Measurements and Fuzzy Logic Decision-Making
by Eustachio Roberto Matera, Olivier Lagrange and Maxime Olivier
Eng. Proc. 2026, 126(1), 18; https://doi.org/10.3390/engproc2026126018 - 24 Feb 2026
Viewed by 394
Abstract
Global Navigation Satellite Systems are vulnerable to jamming and spoofing threats, compromising several critical applications. Existing detection methods based on hardware solutions (antenna array, spectrogram) are low-latency and accurate but require expensive hardware, while machine learning solutions are the most effective but require [...] Read more.
Global Navigation Satellite Systems are vulnerable to jamming and spoofing threats, compromising several critical applications. Existing detection methods based on hardware solutions (antenna array, spectrogram) are low-latency and accurate but require expensive hardware, while machine learning solutions are the most effective but require extensive training and lack adaptability. This work proposes an edge-based, statistical threat detector using crowdsourced GNSS data and fuzzy logic to integrate multiple anomaly indicators. A key feature is a C-/N0-based crowdsourcing metric. Experiments show detection precision up to 88% for jamming and 97% for spoofing, with false positive rates around 1–2% and an average detection time of 10 s. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 521 KB  
Proceeding Paper
Enhancing Maritime Navigation: A Novel Approach to Validate GNSS Solutions with a Single R-Mode Station
by Filippo Giacomo Rizzi, Lars Grundhöfer, Stefan Gewies and Niklas Hehenkamp
Eng. Proc. 2026, 126(1), 19; https://doi.org/10.3390/engproc2026126019 - 13 Feb 2026
Viewed by 286
Abstract
The reliance on global navigation satellite systems (GNSS) for modern vessel poses a critical point of failure. GNSS is vulnerable to jamming, spoofing, and other threats that can increase the risk of accidents. In response, alternative sources of navigational information are being sought. [...] Read more.
The reliance on global navigation satellite systems (GNSS) for modern vessel poses a critical point of failure. GNSS is vulnerable to jamming, spoofing, and other threats that can increase the risk of accidents. In response, alternative sources of navigational information are being sought. R-Mode offers a promising solution by leveraging terrestrial infrastructure to provide PNT data independently of GNSS. A minimum of three stations in view is needed to obtain a position and timing information. While a single R-Mode station in view cannot provide independent positioning, the received data can still be used to validate a GNSS solutions and detect threats like spoofing or outages. In this study, we introduce a novel approach to validate GNSS positions using R-Mode ranging information from a single station by combining the expected accuracy of the measurements with the geometrical relationship between the GNSS solution and the known R-Mode transmitter location. Our method was tested with real measurements in post-processing, where simulated spoofing events were introduced to mimic real-world scenarios. During these events, the GNSS solution deviated by approximately 100 m from original position. Our technique successfully detected the spoofing instances and raised warnings to increase the awareness of GNSS-based navigation threats. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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11 pages, 1833 KB  
Proceeding Paper
Jammertest: An Open GNSS Interference Test Arena to Accelerate the Development of Resilient GNSS Applications
by Nicolai Gerrard, Tor Atle Solend, Anders Rødningsby, Øystein Karlsen, Tomas Levin, Harald Hauglin, Kristian Svartveit, Christian Berg Skjetne, Anders Martin Solberg, Thomas Rødningen and Øystein Borlaug
Eng. Proc. 2026, 126(1), 20; https://doi.org/10.3390/engproc2026126020 - 24 Feb 2026
Viewed by 2908
Abstract
Jammertest, held annually in Andøya, Northern Norway, is the world’s largest open test for evaluating the resilience of Global Navigation Satellite System (GNSS) technologies against jamming, meaconing, and spoofing threats. Set in a remote Arctic location ideal for high-power interference testing with minimal [...] Read more.
Jammertest, held annually in Andøya, Northern Norway, is the world’s largest open test for evaluating the resilience of Global Navigation Satellite System (GNSS) technologies against jamming, meaconing, and spoofing threats. Set in a remote Arctic location ideal for high-power interference testing with minimal societal impact, the event brings together a wide range of participants, from academia and industry to government agencies, to conduct real-world GNSS interference testing from a comprehensive and up-to-date Test Catalogue. Organised by a coalition of Norwegian authorities, Jammertest offers a unique environment and an inclusive approach to foster advancements in GNSS resilience without relying on strict regulation. This paper describes the background, approach, and technical setup, such as the transmissions, for the test week. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 10777 KB  
Proceeding Paper
Blender-Based Simulation and Evaluation Framework for GNSS-LiDAR Sensor Fusion
by Adam Kalisz, Muhammad Khalil, Iñigo Cortés, Santiago Urquijo, Katrin Dietmayer, Matthias Overbeck, Christoph Miksovsky and Alexander Rügamer
Eng. Proc. 2026, 126(1), 21; https://doi.org/10.3390/engproc2026126021 - 14 Feb 2026
Viewed by 328
Abstract
The fusion of Global Navigation Satellite System (GNSS) and Light Detection and Ranging (LiDAR) sensors has emerged as a critical research area for high-precision navigation and mapping applications. While GNSS provides absolute positioning, it is susceptible to multipath errors, signal occlusions, and atmospheric [...] Read more.
The fusion of Global Navigation Satellite System (GNSS) and Light Detection and Ranging (LiDAR) sensors has emerged as a critical research area for high-precision navigation and mapping applications. While GNSS provides absolute positioning, it is susceptible to multipath errors, signal occlusions, and atmospheric disturbances. LiDAR, on the other hand, offers high-resolution environmental perception but lacks absolute localization and is sensitive to sensor noise and drift over time. To address these limitations, robust sensor fusion architectures are necessary to improve positioning accuracy, reliability, and robustness in diverse environments. This research focuses on the systematic modeling of GNSS and LiDAR errors to enhance sensor fusion performance. A key aspect of this work is the design of fusion architectures that optimize trade-offs between accuracy, environmental-dependency, and robustness to sensor failures. To this end, this research investigates trajectory alignment, geometric similarity, and sensor signal dropouts. Various fusion strategies, including tightly coupled and loosely coupled approaches, are explored to evaluate their effectiveness under different operational conditions. Simulation-based evaluation is a core component of this study, enabling controlled analysis of sensor errors, fusion methodologies, and performance metrics. A custom Blender-based simulation framework has been developed to facilitate reproducible experiments and allow for the benchmarking of different fusion strategies. By systematically analyzing fusion performance in terms of accuracy, consistency, and computational cost, this work aims to provide valuable insights into the optimal integration of GNSS and LiDAR for real-world applications. The simulation framework generates a reusable output format in order to demonstrate the flexibility of this methodology by running a selected fusion approach on real data (Sim2Real). The proposed framework and findings contribute to the research community by providing tools and methodologies for evaluating sensor fusion strategies, fostering advancements in precise and resilient localization solutions for autonomous systems, robotics, and geospatial applications in challenging environments. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 623 KB  
Proceeding Paper
Estimation of Gravity Gradients Using Deep Learning for Efficient Positioning with a Quantum Sensor
by Daniel J. Chadwick, Michael Wright, Kirsty McKay, Grant MacLean and Jason F. Ralph
Eng. Proc. 2026, 126(1), 22; https://doi.org/10.3390/engproc2026126022 - 24 Feb 2026
Viewed by 727
Abstract
Quantum cold-atom sensors provide precise measurements of gravitational acceleration and gravity gradients. By matching these measurements to a high-resolution gravity database, a moving platform can derive its position using map-matching techniques that fuse gradient observations with inertial navigation. One such fusion technique, particle [...] Read more.
Quantum cold-atom sensors provide precise measurements of gravitational acceleration and gravity gradients. By matching these measurements to a high-resolution gravity database, a moving platform can derive its position using map-matching techniques that fuse gradient observations with inertial navigation. One such fusion technique, particle filters, is dominated by the cost of evaluating gravity gradients via surface integrals at each location. To overcome this overhead, we introduce a deep-learning model that predicts the vertical gravity gradient from a compact subset of local gravity anomaly samples, eliminating the need for full integral computations. We integrate this deep neural network into the map-matching framework, benchmark its accuracy against conventional methods, and demonstrate its real-time performance within a simulated inertial navigation system driven by a quantum sensor model. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 4062 KB  
Proceeding Paper
Alternative Navigation Approaches for Railways: Overcoming GNSS Limitations
by Jakub Steiner, Timo Pech, Tomáš Duša, Klaus Mößner and Mária Kmošková
Eng. Proc. 2026, 126(1), 23; https://doi.org/10.3390/engproc2026126023 - 25 Feb 2026
Viewed by 624
Abstract
Accurate and reliable train localization is critical for rail safety, particularly on regional and rural lines where traditional track-based infrastructure (e.g., balises, track circuits) is often too costly. Global Navigation Satellite Systems (GNSSs) offer a potential solution, but their performance degrades significantly in [...] Read more.
Accurate and reliable train localization is critical for rail safety, particularly on regional and rural lines where traditional track-based infrastructure (e.g., balises, track circuits) is often too costly. Global Navigation Satellite Systems (GNSSs) offer a potential solution, but their performance degrades significantly in obstructed environments such as tunnels, forested areas, and deep cuttings commonly present on rail. This study presents a real-world case study of a GNSS-only navigation performance measurement on a regional railway track. Using a mass-market GNSS receiver and a high-precision reference system, the study analyses the position accuracy. Results highlight the limitations of GNSS-only navigation, particularly in meeting accuracy requirements for critical applications such as track distinction. To address these challenges, the study presents a comparative review of Alternative Positioning, Navigation, and Timing (A-PNT) methods. The technology level points to a multi-sensor fusion approach to ensure resilient, cost-effective rail localization for future intelligent and autonomous rail systems. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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8 pages, 913 KB  
Proceeding Paper
Evaluating Smartphone RTK Performance with Low-Cost GNSS Receivers and Correction Services in Traditional and Low-Cost GNSS Networks
by Milad Bagheri, Paolo Dabove and Neil Gogoi
Eng. Proc. 2026, 126(1), 24; https://doi.org/10.3390/engproc2026126024 - 25 Feb 2026
Viewed by 872
Abstract
The emergence of low-cost GNSS hardware and affordable RTK correction services has made high-precision positioning more accessible. While prior studies have investigated RTK capabilities using smartphones, most rely on professional geodetic infrastructures. This study shifts the focus toward evaluating smartphone-based RTK positioning within [...] Read more.
The emergence of low-cost GNSS hardware and affordable RTK correction services has made high-precision positioning more accessible. While prior studies have investigated RTK capabilities using smartphones, most rely on professional geodetic infrastructures. This study shifts the focus toward evaluating smartphone-based RTK positioning within low-cost GNSS networks and comparing the performance against traditional geodetic network setups. The research investigates two main configurations: (1) a smartphone functioning as an RTK rover within a low-cost GNSS network, using a low-cost base station and publicly available or inexpensive correction services, and (2) the same smartphone setup operating within a traditional geodetic network with high-grade base stations. The study aims to assess the viability of smartphones as RTK rovers in low cost networks, exploring metrics such as horizontal and vertical positioning accuracy, fix reliability, initialization time, and system responsiveness. Preliminary findings suggest that smartphones integrated with low-cost GNSS receivers can deliver sub-meter accuracy under favorable conditions, though some trade-offs are noted when compared with geodetic-grade infrastructure. The study emphasizes the potential of cost-effective RTK configurations for practical applications where high precision is required. By comparing performance across traditional and low-cost network configurations, this research demonstrates the increasing potential of using smartphones and low-cost GNSS systems to make high-precision positioning more accessible. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 3625 KB  
Proceeding Paper
A Framework for Integrity Monitoring for Positioning Through Graph-Based SLAM Optimization
by Sam Bekkers and Heiko Engwerda
Eng. Proc. 2026, 126(1), 25; https://doi.org/10.3390/engproc2026126025 - 25 Feb 2026
Viewed by 428
Abstract
As satellite navigation systems show vulnerabilities in specific circumstances such as urban canyons or jamming and spoofing situations, additional sensors such as cameras may be incorporated on the platform. Despite advancements in the robotics and computer vision community, which have led to increasingly [...] Read more.
As satellite navigation systems show vulnerabilities in specific circumstances such as urban canyons or jamming and spoofing situations, additional sensors such as cameras may be incorporated on the platform. Despite advancements in the robotics and computer vision community, which have led to increasingly accurate Simultaneous Localization and Mapping (SLAM) positioning solutions, visual navigation has its own vulnerabilities. It therefore remains of critical importance for many applications to study the integrity of fused navigation algorithms and their components, which is done less for SLAM than for satellite navigation. In this paper, a framework for integrity monitoring (IM) of a visual SLAM algorithm is proposed. A sensor-level IM scheme analyses feature reprojection errors. It is demonstrated that, in dynamic environments, multiple hypotheses can be generated from different subsets of extracted features. Additionally, the factor graph-based framework employs a fusion-level IM scheme which deals with these multiple hypotheses and selects the most probable one by calculating the sum of weighted measurement residuals. These concepts are applied to scenarios from real and simulated experiments in order to demonstrate applicability. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 1872 KB  
Proceeding Paper
A Solution to GNSS-Denied Navigation for Aeronautics—Combining GNSS-Denied Navigation Means and Collaborative Navigation
by Tobias Neuhauser, Talha Ince and Thomas Telaar
Eng. Proc. 2026, 126(1), 26; https://doi.org/10.3390/engproc2026126026 - 26 Feb 2026
Viewed by 692
Abstract
This paper presents how the combination of Vision-based Navigation (VBN), Terrain Referenced Navigation (TRN) and Star Navigation complement each other to tackle the challenge of GNSS-denied navigation for aeronautics covering a wide range of environmental and operational conditions. Moreover, Collaborative Navigation contributes to [...] Read more.
This paper presents how the combination of Vision-based Navigation (VBN), Terrain Referenced Navigation (TRN) and Star Navigation complement each other to tackle the challenge of GNSS-denied navigation for aeronautics covering a wide range of environmental and operational conditions. Moreover, Collaborative Navigation contributes to GNSS-denied navigation capability by distributing the position information within the group of collaborating platforms in a stochastically optimal way using an Extended Kalman Filter. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 1335 KB  
Proceeding Paper
Demonstrating the Broadcast of Authenticated AIS Messages Using VDES While Retaining Backwards Compatibility
by Gareth Wimpenny, Nikolaos Vastardis, Jan Šafář and Chris Hargreaves
Eng. Proc. 2026, 126(1), 27; https://doi.org/10.3390/engproc2026126027 - 25 Feb 2026
Viewed by 575
Abstract
The spoofing of Automatic Identification System (AIS) messages presents a hazard to safe maritime navigation. To prevent such spoofing, we present an authentication system based on Public Key Cryptography (PKC) that is both fully open source and backwards compatible with mariners’ existing use [...] Read more.
The spoofing of Automatic Identification System (AIS) messages presents a hazard to safe maritime navigation. To prevent such spoofing, we present an authentication system based on Public Key Cryptography (PKC) that is both fully open source and backwards compatible with mariners’ existing use of the AIS. Using this, we have successfully demonstrated the ‘live’, over-the-air broadcast of authenticated AIS messages in a busy radio environment. The technique used is an improvement upon earlier work in that digital signatures are carried using the terrestrial VHF Data Exchange (VDE-TER) component of the VHF Data Exchange System (VDES). This prevents additional channel loading on the AIS and offers greater flexibility. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 2455 KB  
Proceeding Paper
Abnormal Performance Monitoring Algorithm for Dual Single-Axis RINSs Redundant System in the Reference Information Absence
by Yuanhan Wang, Zhonghong Liang, Pengcheng Mu, Ming Tian, Zhikun Liao and Lin Wang
Eng. Proc. 2026, 126(1), 28; https://doi.org/10.3390/engproc2026126028 - 25 Feb 2026
Viewed by 242
Abstract
Rotational inertial navigation systems (RINSs) are often employed in long-endurance navigation due to their high-precision characteristics. A redundant configuration is often adopted in practice to cope with potential faults. To effectively monitor the dual single-axis RINSs redundant system, this paper proposes a novel [...] Read more.
Rotational inertial navigation systems (RINSs) are often employed in long-endurance navigation due to their high-precision characteristics. A redundant configuration is often adopted in practice to cope with potential faults. To effectively monitor the dual single-axis RINSs redundant system, this paper proposes a novel real-time fault monitoring algorithm that integrates adaptive filtering with parameter estimation. The adaptive fault monitoring filter based on the state transformation error model with attitude observations increases the sensitivity of the filter to potential faults. Based on analysis of the filter estimation, a robust fault diagnosis criterion is proposed. Furthermore, the drift variation fitting mechanism is further proposed to address the challenge in monitoring faults of azimuth gyros. Experiments conclusively demonstrate the proficiency of the proposed method in achieving precise and swift fault monitoring. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 2524 KB  
Proceeding Paper
Wide-Area GNSS Interference Source Localization Using a Sparse Monitoring Network
by Aiden Morrison and Nadezda Sokolova
Eng. Proc. 2026, 126(1), 29; https://doi.org/10.3390/engproc2026126029 - 25 Feb 2026
Viewed by 1073
Abstract
This paper discusses the design, development, and initial testing of a distributed monitoring system intended to detect and localize sources of harmful interference impacting Global Navigation Satellite System (GNSS) users over city-sized areas using only a small number of monitoring stations to limit [...] Read more.
This paper discusses the design, development, and initial testing of a distributed monitoring system intended to detect and localize sources of harmful interference impacting Global Navigation Satellite System (GNSS) users over city-sized areas using only a small number of monitoring stations to limit costs. The motivation and background of the work is rooted in the results of the Advanced Radio Frequency Interference Detection Analysis and Alerting System (ARFIDAAS), a network of GNSS Radio Frequency Interference (RFI) monitors which built the largest known database of multi-frequency GNSS RFI events. Insights gained from this database on parameters such as modulations, impacted bands, power-level distributions and other relevant factors are used to inform the design of the source localization system discussed in the paper. The design of the receiver hardware to allow the implementation of a distributed Time Difference of Arrival (TDOA) detection and localization system incorporating components of Commercial Off-The-Shelf (COTS) radios while supporting dynamic coverage of all L-band signals is detailed, along with the software architecture used to control and operate the individual nodes of the work-in-progress development systems and testbed. Further information is included to describe the design and operation of the software which controls the composite network, including decisions made for the support of mobile detectors and multiple data consumers to allow the pursuit of multiple simultaneous sources. Since the system is designed for the detection of sources which are likely below the local noise floor at the participating nodes, the paper explores the derived operating envelope of the architecture, showing examples of measurements produced during controlled field testing at Jammertest 2023, and discusses considerations for the screening of nuisance events that are likely to be unintentionally generated by incidental devices over a city-sized area. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 1571 KB  
Proceeding Paper
GNSS Pseudorange Differencing for Relative Train Positioning: Performance Assessment in a Railway Environment
by Enki Saura, Alex Minetto, Fabio Dovis and Juliette Marais
Eng. Proc. 2026, 126(1), 30; https://doi.org/10.3390/engproc2026126030 - 25 Feb 2026
Viewed by 339
Abstract
Capillary railway lines, though vital for regional development, face economic challenges due to high infrastructure costs. Replacing trackside sensors with onboard GNSS-based positioning offers a cost-effective solution, but standard GNSS methods struggle to meet stringent railway safety standards. This study explores GNSS pseudorange [...] Read more.
Capillary railway lines, though vital for regional development, face economic challenges due to high infrastructure costs. Replacing trackside sensors with onboard GNSS-based positioning offers a cost-effective solution, but standard GNSS methods struggle to meet stringent railway safety standards. This study explores GNSS pseudorange differencing—a relative positioning technique that mitigates common GNSS errors and enables its application in train collision avoidance systems without necessitating full system certification. We present mathematical formulations for several differencing methods and validate them through real-world experiments on a capillary railway line using a light train. Results confirm that horizontal differencing improves accuracy, robustness, and relative speed estimation, supporting its potential for infrastructure-light, safety-critical rail applications. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 2301 KB  
Proceeding Paper
Development of a Star Classifier for Optimal Geopositioning Purposes Using a Star-Sighting Device
by Guillaume Rance and Philippe Élie
Eng. Proc. 2026, 126(1), 31; https://doi.org/10.3390/engproc2026126031 - 25 Feb 2026
Viewed by 310
Abstract
In environments where Global Navigation Satellite Systems are denied, a common solution to estimate one’s position on the Earth is to use stars as inertial references, as was done centuries ago by navigators using a sextant. Nowadays, sextants have been replaced by star-sighting [...] Read more.
In environments where Global Navigation Satellite Systems are denied, a common solution to estimate one’s position on the Earth is to use stars as inertial references, as was done centuries ago by navigators using a sextant. Nowadays, sextants have been replaced by star-sighting devices, composed of inertial sensors, precise clocks, and one or more star sensors, combining the short-term precision of inertial navigation techniques and the long-term precision of celestial ones. In this context, this paper aims at developing a star classifier for geopositioning purposes, i.e., a way to discriminate stars in the sky so that an observer can choose the stars that would provide the most precise estimate of their position regarding the sighting performances of the device used (sensor definition, precision of the inertial sensor, etc.). The star classifier proposed in this paper is based on differential calculations and spherical trigonometry, and leads to closed-form expressions that are easily embeddable to evaluate the potential of a star. These closed-form expressions are then validated on an experimental setup. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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11 pages, 565 KB  
Proceeding Paper
Reinforcement Learning-Driven GNSS Observation Selection for Enhanced PPP Accuracy
by Álvaro Tena, María Crespo, Adrián Chamorro, Alberto Díaz-Álvarez, Víctor Rodríguez-Fernández and Ana González
Eng. Proc. 2026, 126(1), 32; https://doi.org/10.3390/engproc2026126032 - 3 Mar 2026
Viewed by 431
Abstract
This work presents a reinforcement learning (RL) framework integrated into GMV’s GSharp® precise point positioning (PPP) algorithm to optimize GNSS measurement processing. Initially developed for multipath mitigation, the RL agent has evolved into a decision-making tool that evaluates the usefulness of GNSS [...] Read more.
This work presents a reinforcement learning (RL) framework integrated into GMV’s GSharp® precise point positioning (PPP) algorithm to optimize GNSS measurement processing. Initially developed for multipath mitigation, the RL agent has evolved into a decision-making tool that evaluates the usefulness of GNSS observations to enhance positioning accuracy. The model processes GNSS data epoch by epoch using features such as pseudoranges, signal-to-noise ratios, elevation angles, and residuals. Based on these inputs, the agent decides whether each measurement should be included in the positioning solution. A custom reward function encourages decisions that reduce positioning error while maintaining solution stability. The system was trained on over 50 h of GNSS raw data collected in diverse environments, including urban canyons, suburban areas, and open spaces, promoting generalization across real-world conditions. Preliminary validation shows that the RL-enhanced PPP algorithm achieves accuracy improvements over the baseline GSharp® solution in several challenging scenarios. These results suggest that RL can support GNSS data processing by adaptively managing the quality and relevance of observations, potentially enabling more robust and precise positioning in complex environments. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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13 pages, 537 KB  
Proceeding Paper
Assessment of Lunar User PVT Performances Tightly Coupling Moonlight Signal with IMU Measurements
by Yoann Audet, Michele Ceresoli, Floor T. Melman, Dimitrios V. Psychas, Richard D. Swinden, Cosimo Stallo, Monica Gotta and Javier Ventura-Traveset
Eng. Proc. 2026, 126(1), 33; https://doi.org/10.3390/engproc2026126033 - 3 Mar 2026
Viewed by 1236
Abstract
With the renewed interest in lunar exploration, evidenced by the increasing number of planned missions over the past decade, space agencies are investing in dedicated lunar communication and navigation systems, such as the European Space Agency’s (ESA) Moonlight Lunar Communication and Navigation System [...] Read more.
With the renewed interest in lunar exploration, evidenced by the increasing number of planned missions over the past decade, space agencies are investing in dedicated lunar communication and navigation systems, such as the European Space Agency’s (ESA) Moonlight Lunar Communication and Navigation System (LCNS), to support various types of missions. Other space agencies, such as NASA and JAXA, are also foreseeing to deploy similar infrastructure, which will all be interoperable according to the LunaNet Specification. One of the critical phases in both human and robotic lunar exploration is the landing of spacecrafts on the Moon’s surface. This operation is complex and challenging, as demonstrated by recent crashes like the Luna25 lander from the Russian Space Agency or the Intuitive Machine private lander. Reliable positioning capabilities during descent are among the various services offered by dedicated lunar navigation systems and shall enable safe and reliable landing to a 90 metres 3-sigma landing accuracy from a target point, as defined by the Global Exploration Roadmap Critical Technology Needs. Faulty landings can be due to several causes. This paper examines the achievable positioning accuracy for a lander targeting the Moon’s South Pole using satellite-based navigation services like Moonlight and how the impact of faulty sensors (such as a faulty IMU) can be mitigated using Moonlight LCNS. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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11 pages, 2655 KB  
Proceeding Paper
Realistic Tropospheric Delay Modeling Based on Machine Learning for Safran’s Skydel-Powered GNSS Simulators
by Theo Carbillet, Yvan Mezencev, Mohamed Tamazin and Pierre-Marie Le Véel
Eng. Proc. 2026, 126(1), 34; https://doi.org/10.3390/engproc2026126034 - 4 Mar 2026
Viewed by 516
Abstract
Accurate modeling of tropospheric effects on GNSS signals is essential for achieving high-precision positioning, as the troposphere can delay pseudorange signals by up to 30 m in Standard Point Positioning applications. While empirical models, such as the Saastamoinen model, are commonly used to [...] Read more.
Accurate modeling of tropospheric effects on GNSS signals is essential for achieving high-precision positioning, as the troposphere can delay pseudorange signals by up to 30 m in Standard Point Positioning applications. While empirical models, such as the Saastamoinen model, are commonly used to simulate tropospheric delay by separating it into the hydrostatic (ZHD) and wet (ZWD) components, these models often lack the realism needed to model the highly variable ZWD accurately. To address this limitation, Safran Electronics & Defense has developed an advanced machine learning-based model to enhance the realism of the unpredicted ZWD simulation within the Skydel-powered GNSS simulators. The model incorporates a feedforward neural network with two hidden layers, integrated with empirical methods for ZHD computation, resulting in a robust hybrid framework. The model is trained on a comprehensive 20-year dataset (2004–2024) collected from 221 GNSS stations worldwide and further refined using meteorological data from Open Meteo to ensure accurate input parameters. This innovative hybrid approach significantly enhances the realism of tropospheric delay modeling for Safran’s Skydel GNSS simulation software (version 24.4). Performance evaluations show a significant reduction in simulation errors across all tested stations, especially under complex and dynamic weather conditions. The paper details the new model’s design, training, and optimization processes, emphasizing the seamless integration of machine learning techniques within the Skydel simulator architecture. By delivering more realistic simulations, this methodology enhances the fidelity of GNSS signal modeling and establishes a new benchmark for the integration of machine learning into reliable GNSS simulators. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 6221 KB  
Proceeding Paper
Feasibility of AI Feature Recognition-Aided PNT in GNSS-Challenged Environments
by Jelena Gabela and Ivan Majić
Eng. Proc. 2026, 126(1), 35; https://doi.org/10.3390/engproc2026126035 - 5 Mar 2026
Viewed by 481
Abstract
Positioning, Navigation and Timing (PNT) methods in GNSS-challenged environments require multi-sensor and cooperative approaches to mitigate the low or complete unavailability of GNSS measurements. Many methods also rely on map databases and the availability of sensors throughout the environment. Data like Signal of [...] Read more.
Positioning, Navigation and Timing (PNT) methods in GNSS-challenged environments require multi-sensor and cooperative approaches to mitigate the low or complete unavailability of GNSS measurements. Many methods also rely on map databases and the availability of sensors throughout the environment. Data like Signal of Opportunity (SoO) ranges, Inertial Measurement Units, and camera data are often used to ensure measurement redundancy. Given the recent advancements in Artificial Intelligence (AI) image segmentation, especially the Segment Anything Model (SAM) and Depth Anything (DA) model, there is an opportunity to treat AI as a modern SoO. SAM can quickly and efficiently recognise distinct objects in any image, while DA can create a pixel-based depth map from any image. A novel architecture for combining multi-sensor cooperative positioning and a position integrity method with SAM and DA is proposed. In this paper, the initial feasibility study of using SAM and DA to determine the ranges from images is carried out. SAM and DA are tested on photographs taken in Vienna, Austria. The feasibility of establishing a functional relation between determined depth and ground truth distances is studied and demonstrated. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 2913 KB  
Proceeding Paper
Towards Safe Localisation for Railways: Results from the EGNSS MATE Project
by Andreas Wenz, Michael Roth, Paulo Mendes, Roman Ehrler, Andreas Bomonti, Nikolas Dütsch, Camille Parra, Toms Dorins, Alice Martin, Judith Heusel and Keivan Kiyanfar
Eng. Proc. 2026, 126(1), 36; https://doi.org/10.3390/engproc2026126036 - 6 Mar 2026
Viewed by 435
Abstract
Safe train positioning is a key technology to make rail transportation more efficient and cost-effective. Within the EGNSS MATE project, the project partners SBB, DLR, and IABG researched the use of European Global Satellite Navigation Systems for this application. The main contributions are [...] Read more.
Safe train positioning is a key technology to make rail transportation more efficient and cost-effective. Within the EGNSS MATE project, the project partners SBB, DLR, and IABG researched the use of European Global Satellite Navigation Systems for this application. The main contributions are the development of a novel map-based sensor fusion algorithm, the development of a test catalogue for jamming and spoofing cyberthreats, and the collection of a large and rich dataset for testing and validation. The dataset includes over 200 h of sensor data and ground truth data, covering most of the Swiss normal gauge network. In addition, tests were conducted to assess the impact of jamming and spoofing attacks. Results show promising performance of the algorithms on most of the lines, excluding some long tunnels and sections with heavy multipath. The findings of the project results will help to introduce safe train positioning into ETCS by boosting development and standardisation efforts. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 1397 KB  
Proceeding Paper
Transmission of Ionospheric Parameters in Galileo HAS Phase 2
by Tom Willems, Ignacio Fernandez-Hernandez, Jon Winkel, Cillian O’Driscoll, Marc Mattis, Paolo Zoccarato, Jose Miguel Juan, Jaume Sanz, Adria Rovira and Cristhian Timote
Eng. Proc. 2026, 126(1), 37; https://doi.org/10.3390/engproc2026126037 - 10 Mar 2026
Viewed by 336
Abstract
The Galileo High Accuracy Service (HAS) has been operational since January 2023, offering good and stable performance. The next phase of HAS is currently being implemented, offering enhanced performance and new functionalities. One of the improvements in HAS Phase 2 will be the [...] Read more.
The Galileo High Accuracy Service (HAS) has been operational since January 2023, offering good and stable performance. The next phase of HAS is currently being implemented, offering enhanced performance and new functionalities. One of the improvements in HAS Phase 2 will be the provisioning of ionospheric parameters to users in the European Coverage Area (ECA). This paper focuses on the new Message Type 2 (MT2) which will contain the ionospheric parameters, i.e., ionospheric vertical delays (IVDs) and ionospheric vertical accuracies (IVAs). IVDs and IVAs will be provided for ionospheric grid points (IGPs) which receivers in the ECA can see down to a certain elevation. Data for two ionospheric layers is planned to be provided. Because transmitting the IVDs and IVAs for a vast number of IGPs requires a significant amount of bandwidth, an investigation was also launched into different approaches for compressing the IVD data. To assess the efficacy of the compression, the percentage decrease in size was assessed through post-processing of historical data. Compared to non-optimized encoding of the IVDs using a fixed number of bits, processing of historical data showed a median IVD block size reduction of about 27% and 41% under solar maximum and solar minimum conditions, respectively. The IVD block compression approach will be evaluated further during the HAS Phase 2 implementation. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 3612 KB  
Proceeding Paper
Fault Diagnosis Algorithm for Redundant Dual-Axis RINSs Based on Geometric Constraint Observation
by Zhonghong Liang, Hui Luo, Yuanhan Wang, Pengcheng Mu, Yong Ruan, Zhikun Liao and Lin Wang
Eng. Proc. 2026, 126(1), 38; https://doi.org/10.3390/engproc2026126038 - 10 Mar 2026
Viewed by 218
Abstract
Dual-axis rotational inertial navigation systems (DRINSs) have been widely used in marine navigation due to their high accuracy. However, the long-term operation of a DRINS over weeks poses a significant challenge to its reliability. In order to address the fault diagnosis challenges faced [...] Read more.
Dual-axis rotational inertial navigation systems (DRINSs) have been widely used in marine navigation due to their high accuracy. However, the long-term operation of a DRINS over weeks poses a significant challenge to its reliability. In order to address the fault diagnosis challenges faced by DRINSs on long-endurance vessels in global navigation satellite system (GNSS)-denied environments, this paper proposes a fault diagnosis algorithm for redundant DRINSs based on geometric constraint observation. The mechanization of dual DRINSs is implemented using a globally referenced framework. A residual-normalized strong tracking filter based on geometric constraint observation is employed to estimate the fault states of the dual DRINSs. A highly robust fault diagnosis method is proposed to detect and diagnose faults in the inertial devices of dual DRINSs. The experimental results show that the proposed algorithm exhibits excellent performance with a diagnostic accuracy of 98.67% and low diagnostic delay. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 5612 KB  
Proceeding Paper
First Test of a Multi-Constellation, Multi-Frequency GNSS Receiver on Board a Sounding Rocket
by Benjamin Braun, Markus Markgraf, Lennart Rheinwald, Sebastian Weiß and Marcus Hörschgen-Eggers
Eng. Proc. 2026, 126(1), 39; https://doi.org/10.3390/engproc2026126039 - 13 Mar 2026
Viewed by 455
Abstract
The paper shows the results of a first test of two multi-constellation, multi-frequency GNSS receivers on board the MAPHEUS-15 sounding rocket, which was launched from Esrange, Sweden, on 11 November 2024. During the flight, the GNSS receivers tracked the signals from up to [...] Read more.
The paper shows the results of a first test of two multi-constellation, multi-frequency GNSS receivers on board the MAPHEUS-15 sounding rocket, which was launched from Esrange, Sweden, on 11 November 2024. During the flight, the GNSS receivers tracked the signals from up to 37 satellites simultaneously and were thus able to continuously compute a navigation solution from lift-off until atmospheric reentry and during the landing phase on the parachute, even in the presence of jamming. The flight test showed that the robustness of the navigation solution could be noticeably improved by increasing the number of constellations and signals. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 1881 KB  
Proceeding Paper
Prototyping Galileo Signal Authentication Service: Current Status and Plans
by Ignacio Fernandez-Hernandez, Jon Winkel, Cillian O’Driscoll, Tom Willems, Simon Cancela, Miguel Alejandro Ramirez, Rafael Terris-Gallego, Jose A. Lopez-Salcedo, Gonzalo Seco-Granados, Florian Fuchs, Gianluca Caparra, Daniel Blonski, Beatrice Motella, Aleix Galan and Javier Simon
Eng. Proc. 2026, 126(1), 40; https://doi.org/10.3390/engproc2026126040 - 16 Mar 2026
Viewed by 552
Abstract
The Galileo Signal Authentication Service (SAS) is the next new feature to be offered by Galileo, the European GNSS. Its signal-in-space initial capability is expected already in the next months of 2025, starting with the L3 (Launch 3) Galileo elliptical-orbit satellites. It is [...] Read more.
The Galileo Signal Authentication Service (SAS) is the next new feature to be offered by Galileo, the European GNSS. Its signal-in-space initial capability is expected already in the next months of 2025, starting with the L3 (Launch 3) Galileo elliptical-orbit satellites. It is the first-ever navigation signal authentication feature offered globally and openly. Galileo SAS uses the existing Galileo E6-C signal to be encrypted, in combination with OSNMA (Open Service Navigation Message Authentication), through the so-called semi-assisted authentication concept. In this concept, portions of the E6-C are re-encrypted with OSNMA future keys and published in a server. The concept allows signal authentication openly and for free, and without private key management by users. In exchange, the time between authentications is 30 s, inherited from OSNMA, and it introduces a latency between the E6-C signal reception and its authentication down to a few seconds. This work presents the status of Galileo SAS. It outlines its latest technical definition, already shared in previous publications. It will also present the MMARIO (Message and Measurement Authentication Receiver for Initial Operations) project, developing the first SAS server, receiver and testing platform. The paper also outlines the Galileo SAS plans for the near future, up to the Initial Service Declaration. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 888 KB  
Proceeding Paper
Performance Assessment of Multi-RIS-Aided Localization in Non-Terrestrial Networks
by Daniel Egea-Roca, Alda Xhafa, José A. López-Salcedo and Gonzalo Seco-Granados
Eng. Proc. 2026, 126(1), 41; https://doi.org/10.3390/engproc2026126041 - 23 Mar 2026
Cited by 1 | Viewed by 331
Abstract
The increasing demand for global connectivity has accelerated the integration of non-terrestrial networks (NTNs), particularly low Earth orbit (LEO) satellite constellations, into next-generation position navigation and time (PNT) systems. While LEO-based PNT offers low-latency and high-accuracy potential, challenges such as high path loss [...] Read more.
The increasing demand for global connectivity has accelerated the integration of non-terrestrial networks (NTNs), particularly low Earth orbit (LEO) satellite constellations, into next-generation position navigation and time (PNT) systems. While LEO-based PNT offers low-latency and high-accuracy potential, challenges such as high path loss and limited ground-level signal diversity remain. Reconfigurable intelligent surfaces (RISs) have emerged as a cost-effective solution to enhance localization performance by providing controllable reflections with minimal infrastructure. Building on prior work in single-RIS NTN scenarios, this paper investigates RIS-aided localization in a single-LEO PNT setting with multiple RISs. We introduce a detailed signal model and multi-stage processing framework that estimates both the satellite and RIS-assisted paths, enabling accurate receiver localization. Simulations assess the trade-offs in coverage and accuracy, providing insights into the feasibility and optimization of RIS-assisted NTN PNT solutions as a complementary alternative to global navigation satellite system (GNSS). Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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8 pages, 528 KB  
Proceeding Paper
Constrained 1D Localization for Downlink TDoA-Based UWB RTLS
by Václav Navrátil and Josef Krška
Eng. Proc. 2026, 126(1), 42; https://doi.org/10.3390/engproc2026126042 - 27 Mar 2026
Viewed by 433
Abstract
The current development of ultra-wide band localization systems focuses on reducing the number of infrastructure nodes (anchors). In certain areas and applications the full three-dimensional position is not necessary; therefore, constraining the solution brings an opportunity to use fewer anchors. In this work, [...] Read more.
The current development of ultra-wide band localization systems focuses on reducing the number of infrastructure nodes (anchors). In certain areas and applications the full three-dimensional position is not necessary; therefore, constraining the solution brings an opportunity to use fewer anchors. In this work, soft constraining of lateral and vertical position components for Time Difference of Arrival positioning in a corridor-like scenario is presented. Implementation in extended and unscented Kalman filter solvers is described. Tests in a real environment suggests that the constraints enable reliable along-track position estimation even with two or three anchors in sight, and the accuracy is better than 30 cm (RMS). Moreover, the soft nature of constraints allows for uncertainty in the constraint definition. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 2959 KB  
Proceeding Paper
AI-Driven Detection, Characterization and Localization of GNSS Interference: A Comprehensive Approach Using Portable Sensors
by Yasamin Keshmiri Esfandabadi, Amir Tabatabaei and Ruediger Hein
Eng. Proc. 2026, 126(1), 43; https://doi.org/10.3390/engproc2026126043 - 30 Mar 2026
Viewed by 400
Abstract
The increasing interest in the development and integration of navigation and positioning services across a wide range of receivers has exposed them to various security threats, including GNSS jamming and spoofing attacks. Early detection of jamming and spoofing interference is crucial to mitigating [...] Read more.
The increasing interest in the development and integration of navigation and positioning services across a wide range of receivers has exposed them to various security threats, including GNSS jamming and spoofing attacks. Early detection of jamming and spoofing interference is crucial to mitigating these threats and preventing service degradation. This research introduces an interference detection technique leveraging an AI algorithm applied to GNSS data utilizing various methods to enhance detection accuracy and efficiency. The objective was to use modern sensors and AI to develop an effective tool that detects, characterizes, and localizes interference, thereby reducing associated risks. These sensors and algorithms enable continuous GNSS interference monitoring and support real-time Decision-making. A server plays a crucial role in managing the entire system. Its primary function is to process data collected from various sensors referred to as nodes (e.g., static, rover, drone, and space) and from (public) GNSS networks as well as to perform localization using rotating-antenna nodes. Within the interference detection module, various methods were implemented at different points in the software receiver architecture. Each method’s certainty in identifying an interference source depends on its design and capabilities, with outcomes—whether positive or negative—being subject to potential accuracy or errors. To enhance the Decision-making process, an AI-based Decision-making block has been introduced to determine the presence of interference at a given epoch. The proposed interference monitoring methods were evaluated through experiments using GNSS signals under clean, jamming, and spoofing scenarios. The results demonstrate the techniques’ applicability across diverse scenarios, achieving high performance in interference detection, characterization, and localization. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 512 KB  
Proceeding Paper
Multitask Deep Neural Network for IMU Calibration, Denoising, and Dynamic Noise Adaption for Vehicle Navigation
by Frieder Schmid and Jan Fischer
Eng. Proc. 2026, 126(1), 44; https://doi.org/10.3390/engproc2026126044 - 7 Apr 2026
Viewed by 567
Abstract
In intelligent vehicle navigation, efficient sensor data processing and accurate system stabilization is critical to maintain robust performance, especially when GNSS signals are unavailable or unreliable. Classical calibration methods for Inertial Measurement Units (IMUs), such as discrete and system-level calibration, fail to capture [...] Read more.
In intelligent vehicle navigation, efficient sensor data processing and accurate system stabilization is critical to maintain robust performance, especially when GNSS signals are unavailable or unreliable. Classical calibration methods for Inertial Measurement Units (IMUs), such as discrete and system-level calibration, fail to capture time-varying, non-linear, and non-Gaussian noise characteristics. Likewise, Kalman filters typically assume static measurement noise levels for non-holonomic constraints (NHCs), resulting in suboptimal performance in dynamic environments. Furthermore, zero-velocity detection plays a vital role in preventing error accumulation by enabling reliable zero-velocity updates during motion stops, but classical thresholding approaches often lack robustness and precision. To address these limitations, we propose a novel multitask deep neural network (MTDNN) architecture that jointly learns IMU calibration, adaptive noise level estimation for NHC, and zero-velocity detection solely from raw IMU data. This shared-encoder design is utilized to minimize computational overhead, enabling real-time deployment on resource-constrained platforms such as Raspberry Pi. The model is trained using post-processed GNSS-RTK ground truth trajectories obtained from both a proprietary dataset and the publicly available 4Seasons dataset. Experimental results confirm the proposed system’s superior accuracy, efficiency, and real-time capability in GNSS-denied conditions. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 1085 KB  
Proceeding Paper
Active Reconfigurable Intelligent Surface (ARIS)-Empowered Satellite Positioning Approach for Indoor Environments
by Yu Zhang, Xin Sun, Tianwei Hou, Anna Li, Sofie Pollin, Yuanwei Liu and Arumugam Nallanathan
Eng. Proc. 2026, 126(1), 45; https://doi.org/10.3390/engproc2026126045 - 7 Apr 2026
Viewed by 246
Abstract
To mitigate the loss of satellite navigation signals in indoor environments, we propose an active reconfigurable intelligent surface (ARIS)-empowered satellite positioning approach. Deployed on building structures, ARIS reflects navigation signals to indoor receivers to bypass obstructions, providing high-precision positioning services to receivers in [...] Read more.
To mitigate the loss of satellite navigation signals in indoor environments, we propose an active reconfigurable intelligent surface (ARIS)-empowered satellite positioning approach. Deployed on building structures, ARIS reflects navigation signals to indoor receivers to bypass obstructions, providing high-precision positioning services to receivers in non-line-of-sight (NLoS) areas. The path between ARIS and the receiver is defined as the extended line-of-sight (ELoS) path, and an improved carrier phase observation equation is derived to accommodate this path. The receiver compensates for its clock bias through network time synchronization, corrects the actual satellite–ARIS–receiver signal path to the satellite–receiver distance through a distance correction algorithm, and determines the position using the least squares (LS) method. Simulation results show that the proposed method provides positioning services with errors not exceeding 4 m in indoor environments, with time synchronization accuracy within an error range of 10 ns. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 322 KB  
Proceeding Paper
GNSS Interference Along a Highway near an Aircraft Approach Lane: A 5-Month Study
by Julia I. M. Hauser, Roman Lesjak and Hamid Kavousi Ghafi
Eng. Proc. 2026, 126(1), 46; https://doi.org/10.3390/engproc2026126046 - 7 Apr 2026
Viewed by 388
Abstract
Intentional and unintentional GNSS interference can greatly affect the performance of precise timing and localization in areas such as automated driving or aviation. Nevertheless, reports show that jamming occurs near many European airports that are located close to a highway or in heavy [...] Read more.
Intentional and unintentional GNSS interference can greatly affect the performance of precise timing and localization in areas such as automated driving or aviation. Nevertheless, reports show that jamming occurs near many European airports that are located close to a highway or in heavy industry areas due to broadcasting of interfering signals. To assess the impact of such potential risks, we investigated interference occurring on a section of highway located both near to an airport and close to logistics centers as part of the Austrian Security Research Program project CATCH-IN. This section of highway is of particular interest, as the highway runs in parallel to the approach path of aircraft and crosses the approach path 3.7 km before the aircraft touches down (the flight altitude is only 200 m above the ground). For this experiment, we distributed six Septentrio Mosaic x5 GNSS receivers as sensors along the highway and monitored this section for five months. We analyzed the data with AGC monitoring, CN0 monitoring, and baseband sample monitoring to identify interference along the highway that could affect sensors along the descending flight trajectory. During the period of this experiment, we saw events that we believe could cause potential safety risks and problems for aviation safety. In our analysis, we focused on the statistical evaluation of the temporal repetitions, in particular the times of day that see more interference and the frequencies at which more interference occurs. Additionally, we analyzed the performance of different algorithms for dealing with large datasets. The results provide new insight into potential monitoring stations near airports and raise awareness of potential risks and vulnerabilities in aviation safety as well as automated driving along highways. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 298 KB  
Proceeding Paper
Galileo High Accuracy Service: Exploring Atmospheric Corrections and Phase Biases for PPP Performance
by Camille Parra, Urs Hugentobler, Thomas Pany and Stefan Baumann
Eng. Proc. 2026, 126(1), 47; https://doi.org/10.3390/engproc2026126047 - 7 Apr 2026
Viewed by 303
Abstract
The Galileo High Accuracy Service (HAS) provides free-of-charge corrections for PPP through both the E6b signal and the internet. Currently, HAS targets a horizontal and vertical accuracy of 15 cm and 20 cm, respectively (68% confidence level) for static users. Although the service [...] Read more.
The Galileo High Accuracy Service (HAS) provides free-of-charge corrections for PPP through both the E6b signal and the internet. Currently, HAS targets a horizontal and vertical accuracy of 15 cm and 20 cm, respectively (68% confidence level) for static users. Although the service is not yet fully operational, it already delivers orbit and clock corrections, as well as satellite code biases. This paper evaluates the current performance of HAS, showing positioning errors below 5 cm in both horizontal and vertical components. However, the convergence time required to reach these accuracies remains relatively long. To address this limitation, ionospheric corrections were estimated from a European network of 34 stations and added to the processing. The results show a clear improvement in both accuracy and convergence time: horizontal and vertical errors were reduced by half, as well as the horizontal convergence time. To complete the HAS correction set, only satellite phase biases were missing. These were also generated using the same European network. Although no improvement was observed when including them, no degradation was found either. This suggests that, with further refinement, HAS could significantly benefit from phase biases and achieve even better positioning performance. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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8 pages, 2836 KB  
Proceeding Paper
Satellite Navigation in Safety-Critical Decision Making †
by Wili Helenius, Hanna Kajander and Janne Lahtinen
Eng. Proc. 2026, 126(1), 48; https://doi.org/10.3390/engproc2026126048 - 13 Apr 2026
Viewed by 320
Abstract
GPS GNSS position signal manipulation in shipping can lead to significant navigational challenges. Such disruptions may result from various factors, including atmospheric conditions, satellite malfunctions, or intentional positioning satellite signal disturbance. Impacts on shipping operations include delays, increased operational costs, and safety risks [...] Read more.
GPS GNSS position signal manipulation in shipping can lead to significant navigational challenges. Such disruptions may result from various factors, including atmospheric conditions, satellite malfunctions, or intentional positioning satellite signal disturbance. Impacts on shipping operations include delays, increased operational costs, and safety risks for crews and vessels. Understanding these disturbances and their implications is crucial for enhancing maritime safety and efficiency. Common causes of GNSS disturbances in shipping include atmospheric effects such as ionospheric and tropospheric delays, satellite signal obstructions due to terrain or buildings, satellite malfunctions or failures, and intentional interference like jamming. These factors can lead to inaccuracies in positioning, affecting navigation and safety. GPS signals are vulnerable to various cyber threats, including spoofing, jamming, and signal interference. Spoofing involves sending counterfeit GPS signals to mislead receivers, while jamming disrupts the legitimate signals. Ensuring the integrity and security of GPSs is crucial for applications like navigation, timing, and critical infrastructure. Advanced encryption and authentication methods can help safeguard the security of GPS signals. These vulnerabilities can have profound implications for navigation systems and critical infrastructure. Enhancing GPS security requires a combination of advanced technologies and policies to improve signal integrity and authentication processes. The Global Positioning System (GPS) is the most widely used GNSS positioning method in commercial shipping. Moreover, deliberate disturbance technical birth mechanisms are similar across the field of GNSS systems. Therefore, this study focuses on the deliberate disturbance of the GPS, recognising the ability to upscale the research results to other commonly used GNSSs such as Beidou, Galileo, and Glonass. This paper introduces a behavioural approach to enhancing cybersecurity and preparedness to external threats in commercial shipping through European collaboration in the CyberSEA project. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 5259 KB  
Proceeding Paper
Temporal-Correlated Deep Learning-Based GNSS Signal Classification in the Built Environment: A Comparative Experiment
by Lintong Li and Washington Yotto Ochieng
Eng. Proc. 2026, 126(1), 49; https://doi.org/10.3390/engproc2026126049 - 13 Apr 2026
Viewed by 151
Abstract
As a key provider of Positioning, Navigation, and Timing (PNT) information, the characteristics of Global Navigation Satellite System (GNSS) signals, including types, Quality Indicators (QIs), and measurements, should be understood. This study employs temporally correlated deep learning models to classify GNSS signals as [...] Read more.
As a key provider of Positioning, Navigation, and Timing (PNT) information, the characteristics of Global Navigation Satellite System (GNSS) signals, including types, Quality Indicators (QIs), and measurements, should be understood. This study employs temporally correlated deep learning models to classify GNSS signals as Line-of-Sight (LOS) or non-LOS using four QIs: the elevation angle, Carrier to Noise Ratio (C/N0), code measurement’s standard deviation, and difference in azimuth angle. Autocorrelation analysis confirmed that these QIs exhibit significant temporal dependencies. The Bidirectional LSTM (Bi-LSTM) model, with four hidden layers, 64 units, and a sequence length of 18, achieved the best performance: 94.17% classification accuracy and a 2.61% False Positive (FP) rate. Positioning based on classified LOS signals significantly improved accuracy, reducing the mean errors in the horizontal, vertical, and 3D domain by 36.6%, 81.4%, and 59.6%, respectively, and reducing the Standard Deviation (STDEV) by 46.3%, 33.5%, and 45.5%, respectively. Moreover, the non-LOS probability output enables flexible signal selection and mitigates the issue of insufficient signal availability. These results highlight the effectiveness of temporally correlated models in GNSS signal classification and positioning performance. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 4519 KB  
Proceeding Paper
UAV Position Tracking with Ground Cameras
by Andrea Masiero, Paolo Dabove, Vincenzo Di Pietra, Marco Piragnolo, Alberto Guarnieri, Charles Toth, Wioleta Blaszczak-Bak, Jelena Gabela and Kai-Wei Chiang
Eng. Proc. 2026, 126(1), 50; https://doi.org/10.3390/engproc2026126050 - 15 Apr 2026
Viewed by 283
Abstract
The use of Unmanned Aerial Vehicles (UAVs) has become quite popular in several applications during the last few years. Their spread is motivated by the flexibility of usage of UAVs and by their ability to automatically execute several tasks, mostly thanks to the [...] Read more.
The use of Unmanned Aerial Vehicles (UAVs) has become quite popular in several applications during the last few years. Their spread is motivated by the flexibility of usage of UAVs and by their ability to automatically execute several tasks, mostly thanks to the availability of Global Navigation Satellite Systems (GNSSs), which usually allow reliable outdoor localization of aerial vehicles. However, the extension of task automatic execution indoors, and in other challenging working conditions for the GNSS, requires an alternative positioning system able to compensate for the unreliability or unavailability of GNSS in those cases. To this end, additional sensors are usually considered. Among them, cameras are probably the most popular ones. The most common case of a vision-based positioning system is a camera mounted on a moving platform used to determine its ego-motion in a dead-reckoning approach, i.e., visual odometry. Although this solution is affordable and does not require the installation of any infrastructure, it enables absolute positioning of the camera, i.e., of the UAV, only if certain landmarks, with known position, are visible in the flying area. In contrast, this work considers the use of external cameras installed in the flying area to track the UAV movements. This approach is similar to the one implemented in motion capture systems as well, where a set of static cameras is used to triangulate some target positions using calibrated cameras. Instead, this work investigates the use of vision and machine learning tools to (i) extract the UAV position from each video frame and (ii) estimate its 3D position. Estimation of the 3D UAV position is performed with a single camera, exploiting machine learning tools in order to avoid the need for camera calibration. Performance analysis is provided for a dataset collected at the Agripolis campus of the University of Padua. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 1000 KB  
Proceeding Paper
Synthetic Measurements of Triple-Component GNSS Meta-Signals
by Daniele Borio, Melania Susi and Kinga Wȩzka
Eng. Proc. 2026, 126(1), 51; https://doi.org/10.3390/engproc2026126051 - 23 Apr 2026
Viewed by 190
Abstract
The fact that a large Gabor bandwidth promotes measurement accuracy has motivated research on Global Navigation Satellite System (GNSS) meta-signals, which are obtained by jointly processing components from different frequencies. When two side-band components are considered, the resulting meta-signal has characteristics close to [...] Read more.
The fact that a large Gabor bandwidth promotes measurement accuracy has motivated research on Global Navigation Satellite System (GNSS) meta-signals, which are obtained by jointly processing components from different frequencies. When two side-band components are considered, the resulting meta-signal has characteristics close to that of a pure carrier and measurement ambiguities can arise: a third signal in between side-band components can alleviate this problem and help estimating the integer ambiguities. This paper provides a framework for the generation of measurements from triple-component GNSS meta-signals with the goal of reducing the ambiguity problem. The whole meta-signal is at first decomposed as two dual-component meta-signals with the central component used as pivot. Measurements on the dual-component meta-signals are computed using the synthetic approach based on the Hatch-Melbourne-Wübbena (HMW) combination. Triple-component pseudoranges are then obtained as the narrow lane combination of the pseudoranges from the dual-component meta-signals. Theoretical results have been supported through experimental analyses based on measurements from two Septentrio PolaRx5S multi-frequency, multi-constellation receivers set up in a zero-baseline configuration. Results based on the Galileo E5a, E5b and E6 components show the effectiveness of the proposed framework. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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10 pages, 2099 KB  
Proceeding Paper
Error Correction Using Bayesian GRU Network in Hybrid Visual Inertial Navigation System
by Tarafder Elmi Tabassum, Sorin A. Negru, Ivan Petrunin and Zeeshan Rana
Eng. Proc. 2026, 126(1), 52; https://doi.org/10.3390/engproc2026126052 - 28 Apr 2026
Viewed by 216
Abstract
Vision-based navigation systems (VINS) are increasingly utilised as an alternative to GNSS for UAVs operating in urban environments, but they suffer from performance degradation under visual fault conditions like illumination variation, rapid motion, texture-less environments, and weather effects. While hybrid architecture incorporating Kalman [...] Read more.
Vision-based navigation systems (VINS) are increasingly utilised as an alternative to GNSS for UAVs operating in urban environments, but they suffer from performance degradation under visual fault conditions like illumination variation, rapid motion, texture-less environments, and weather effects. While hybrid architecture incorporating Kalman filters and machine learning (ML) improves performance, they often lack evidence of providing contingency for non-Gaussian error distributions, limiting operational safety. To address these shortcomings, an enhanced hybrid VINS architecture is proposed, featuring a Bayesian GRU-based error correction network (B-GRU) to provide a contingency while compensating model errors. To the best of the authors’ knowledge, this is the first attempt to estimate uncertainty using a B-GRU compensator while addressing data uncertainty for VINS applications. The system architecture integrates an Error-State Kalman Filter (ESKF) and the B-GRU, compensating for position errors with uncertainty prediction. The proposed approach is validated using datasets from MATLAB incorporated in an Unreal Engine simulated environment, replicating the complex fault conditions. The ML model is trained on various visual failure modes to adapt the variability in the signal patterns during flights with simulated datasets and tested across varied flight paths and lighting scenarios. The results demonstrate that the fusion strategy effectively corrects erroneous measurements arising from corrupted sensor data and imperfect models and achieves an improvement of 78.06% compared to SOTA hybrid VIO on the horizontal axis while capturing complex flight dynamics in an unseen environment. A comparative analysis demonstrates the effectiveness of B-GRU in mitigating failure modes with a predictive error boundary, achieving a 72% improvement in performance compared to the architecture that integrates GRU-based error compensation. This approach shows a step forward in enhancing positioning accuracy and contingency in challenging urban environments. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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9 pages, 2015 KB  
Proceeding Paper
Celestial Navigation in GNSS-Denied Environment for Aircrafts and Space Rovers
by Maxime Loil, Baptiste Paul, Frédéric Gorog, Johan Montel, Laurent Eychenne and Damien Ponceau
Eng. Proc. 2026, 126(1), 53; https://doi.org/10.3390/engproc2026126053 - 7 May 2026
Viewed by 147
Abstract
In order to enable an autonomous navigation capability in environments where global navigation satellite systems (GNSSs) are either denied (e.g., areas with intentional jamming or spoofing) or not available yet (Moon, Mars), Sodern is currently developing star trackers for Earth-based aircrafts and space [...] Read more.
In order to enable an autonomous navigation capability in environments where global navigation satellite systems (GNSSs) are either denied (e.g., areas with intentional jamming or spoofing) or not available yet (Moon, Mars), Sodern is currently developing star trackers for Earth-based aircrafts and space rovers. This system is designed to compensate for inertial sensor (IMU)-induced drifts by providing an absolute attitude reference. The resulting celestial navigation system (CNS) aims at providing a position evaluation with a 100 m class precision, independent of the mission duration. In this paper, we present the star tracker design with a specific focus on daytime capabilities and the hybridization strategy to implement the retrieved celestial attitude in the CNS. Additionally, we present two application cases currently under development at Sodern, for space rovers and aircrafts. We evaluate the typical performances that can be reached depending on the IMU and star tracker class in harsh environments (luminance, dynamics, radiations…). We conclude with a brief presentation of future developments in this field. Full article
(This article belongs to the Proceedings of European Navigation Conference 2025)
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