The Galileo High Accuracy Service (HAS) enables Precise Point Positioning (PPP) through the broadcast of real-time orbit and clock corrections directly via the Galileo E6 signal. This capability allows for high-precision positioning in flight test environments without any reliance on external data links or ground infrastructure. Such independence makes the service highly attractive for airborne applications where robust and accurate navigation is essential for safety and operational efficiency. However, the reliability of position solutions depends heavily on continuous satellite tracking and often requires a convergence period to reach full accuracy.
In aviation contexts, dynamic maneuvers such as rapid rotations or steep bank angles frequently disrupt the line of sight to Global Navigation Satellite Systems (GNSS) satellites. These disruptions can cause a temporary loss of satellite lock and cycle slips which directly degrade the availability and accuracy of any position solution. To ensure the trustworthiness of the input data, this study introduces an independent satellite integrity monitoring concept. Operating parallel to the position calculation, this concept serves as a Fault Detection and Exclusion (FDE) mechanism designed to safeguard the validity of the PPP input data and to enable the computation of Protection Levels (PLs). It leverages quality indicators and validity flags inherent in the Galileo HAS messages to validate that individual satellite errors remain within specified Alert Limits (AL). By excluding measurements that violate these bounds, the algorithm ensures that the computed PLs accurately reflect the true position uncertainty, similar to the safety guarantees provided by Ground-Based Augmentation Systems (GBAS).
We investigate the behavior of a HAS-enabled receiver during dynamic flight by analyzing recorded flight data that includes both stabilized straight trajectory segments and highly dynamic curved segments. The analysis focuses on quantifying how maneuver dynamics influence satellite continuity and evaluates the integrity concept's performance in efficiently filtering out potentially erroneous measurements. The findings provide insights into the operational limitations of PPP under dynamic conditions. Ultimately, this research demonstrates the potential of utilizing integrity metrics to enhance overall navigation safety by guaranteeing the quality of the raw satellite measurements feeding into the navigation solution.

A terrain-aided navigation (TAN) system is an alternative navigation system primarily designed for environments where radio signal coverage (e.g., the global navigation satellite system or distance measuring equipment) is missing, or its transmission can be accidentally or intentionally interfered with, e.g., jamming or spoofing. TAN systems have been the subject of intensive research for more than seven decades.

Contrary to radio navigation systems, TAN systems determine the position of a vehicle based on statistical processing of onboard sensor measurements and a pre-recorded terrain elevation map of the vehicle's vicinity using, typically, the state estimation algorithms [1, 2]. Thus, TAN systems do not rely on information broadcast to the vehicle remotely and are resistant to interference. Compared to other alternative navigation modalities such as vison, star tracker, or magnetic field navigation, TAN system is all-weather navigation, process publicly available maps, and is generally immune to electromagnetic disturbances. The system exhibits only limited sensitivity to highly localized electromagnetic interference, which is automatically detected and mitigated through advanced monitoring algorithms during processing. On the other hand, the performance of TAN systems depends on the type and profile of the terrain; a flat terrain reduces the navigation performance. Therefore, TAN is often supplemented with dead-reckoning navigation sensors such as an inertial measurement unit (IMU) or odometer, enabling coasting. Combination of TAN with complementary technologies creates a robust and highly reliable solution, ensuring accurate navigation even under challenging conditions.

The paper introduces recently developed prototype of the integrated TAN system for air vehicles, which integrates the IMU and radar altimeter measurements (only) with a terrain map using a proposed computational efficient marginalised grid-based filter. As such, the developed radar altimeter aided TAN (RATAN) provides complete navigation information, including position, velocity, and altitude. In particular, the contribution of the paper is to:
• Provide an overview of the system structure, including a short description of the model and the estimation algorithm,
• Present system performance in a set of trajectories recorded during a campaign flown by fixed wing aircraft in 2025 in the Czech Republic over a wide range of terrain profiles and properties, including analysis of the impact of the surface and elevation maps on TAN accuracy.

References
[1] Nordlund, P., Gustafsson, F.: Nonlinear Kalman filtering techniques for terrain aided navigation. IEEE Transactions on Aerospace and Electronic Systems, vol. 45, no. 4, pp. 1385–1399, 2009.
[2] Dunik, J., Sotak, M., Vesely, M., Straka, O., Hawkinson, W.J.: Design of Rao-Blackwellised point-mass filter with application in terrain aided navigation. IEEE Transactions on Aerospace and Electronic Systems, vol. 55, no 1, pp. 251–272, 2019.
[3] Dunik, J., Sotak, M., Vesely, M., Hawkinson, W.J., Morgan, K.S.: Apparatus and method for terrain aided navigation using inertial position, US Patent Application US 16/522,943, 06 2019.

In recent years, Uncrewed Aerial Vehicles (UAVs) have become an attractive choice to perform river hydrometric data collection flights, as they present many advantages over traditional data collection methods. In the particular case of bathymetry, which consists of measuring and mapping the depth and shape of underwater terrain, UAVs typically fly very close to the water surface (approx. 1 m above). These low-altitude flights often occur beneath overhanging vegetation and close to the riverbanks, which can degrade or interrupt Global Navigation Satellite System (GNSS) signals. Because the accuracy of the resulting bathymetric map depends directly on precise georeferencing, maintaining a robust and accurate positioning solution throughout the flight is critical to ensure reliable bathymetric products.
Therefore, we describe and implement a Post Processed Kinematic (PPK) based Inertial Navigation System (INS) and GNSS Tightly Coupled (TC) algorithm to enable a continuously accurate positioning solution. The proposed solution consists of a Kalman Filter implementation where the error states for position, velocity, attitude and Inertial Measurement Unit (IMU) biases are estimated along with the float ambiguities for the available carrier phase measurements. The measurement model utilizes double differences (measured between the rover and a known base station) and predicted double differences (derived from satellite positions and the INS propagated position of the UAV in between measurement updates). At every iteration of the Kalman Filter, if integer ambiguities can be derived from the estimated float counter partners, these are utilized to correct the position state.
A key challenge in this environment is the adverse impact of vegetation-induced occlusions, refraction, and scattering on GNSS measurements. To address this, the paper explores adaptive and environment-aware GNSS observation weighting strategies aimed at maintaining robust filter performance under varying signal conditions. These strategies include the use of multipath error estimations, carrier-to-noise ratios, and satellite elevation information, as well as filter-based approaches such as adaptive measurement error estimation driven by previous innovations, enabling the navigation solution to respond dynamically to the surrounding environment.
Data was collected with the use of an experimental UAV equipped with an IMU and a GNSS receiver flown in a real river environment in Lyngby, Denmark. Two datasets were collected: one in winter and one in spring, with a noticeable difference in the density of the overhanging vegetation in the riverbanks, to allow for seasonal comparison. For the evaluation, we plan to compare a PPK solution, a code based Tightly Coupled INS/GNSS filter, and the implemented PPK based INS/GNSS filter employing different weighing strategies. To enable a rigorous assessment of the performance of these algorithms, a Leica TS-16 robot total station was used to track a reflective prism on the UAV during the flights, providing a millimeter-level dynamic ground truth in a real river environment.

The Ground-Based Augmentation System (GBAS) is a local, airport-based augmentation of Global Navigation Satellite Systems (GNSS) that provides precision approach and landing guidance for aircraft. By broadcasting differential corrections and integrity information, GBAS enhances GNSS accuracy, integrity, continuity, and availability to meet the stringent safety requirements of precision approach operations.

Recent standardization and research activities have focused on a new dual-frequency, multi-constellation (DFMC) GBAS architecture, known as GBAS Approach Service Type (GAST) E. Unlike current single-frequency systems, GAST E introduces a fundamentally new processing concept in which unsmoothed pseudorange and carrier-phase measurements are transmitted directly from the ground station to the aircraft via the existing VHF Data Broadcast (VDB). The airborne receiver forms a divergence-free (Dfree) linear combination of L1/E1 and L5/E5a measurements and applies an extended smoothing time constant. This approach mitigates ionospheric divergence effects that otherwise accumulate in carrier-smoothing filters, while preserving lower noise and multipath levels than ionosphere-free combinations.

Despite the improved ionospheric robustness of the Dfree concept, integrity monitoring remains essential to detect satellites affected by strong spatial ionospheric gradients. In addition, backward compatibility with legacy GAST C and GAST D users imposes strict constraints on message design, as GAST E must continue to operate within the limited VDB capacity. Recent work has therefore concentrated on optimizing satellite selection, constellation diversity, and transmission rates, together with a ground compression and airborne reconstruction strategy that enables reliable DFMC operation without compromising integrity or availability.

A key new contribution addressed in this paper is the integration of adaptive ground and airborne multipath and noise models into the DFMC GBAS processing chain. These models allow satellites to be used safely before smoothing filters reach steady state—for example after only 10 seconds of smoothing—thereby significantly improving availability and continuity during periods of strong ionospheric scintillation. Both the primary Dfree mode and an ionosphere-free (Ifree) fallback mode are implemented using these adaptive models and the optimized message reconstruction scheme.

The paper presents an assessment of the resulting GAST E architecture performance using real GNSS flight data collected under active ionospheric conditions. The results provide new insight into system behavior in challenging environments and demonstrate the benefits of the proposed adaptive modeling, integrity monitoring, and message optimization concepts for future DFMC GBAS operations.

The rapid deployment of large-scale mega-constellations and the growing density of space missions in Low Earth Orbit (LEO) have intensified concerns regarding collision avoidance, debris mitigation, and the long-term sustainability of the orbital environment. The increasing probability of uncontrolled conjunctions—often associated with the Kessler effect—highlights the urgent need for robust Space Situational Awareness (SSA) capabilities to monitor, track, and manage objects in LEO. Within this context, the Search & Rescue and GNSS for Space Situational Awareness (SARGASSIA) project proposes a cost-effective GNSS-based architecture to enhance SSA functions. This work focuses on one critical component of that architecture: the preliminary design of a Doppler-compensation function for a GNSS-based SSA Active Beacon intended for non-functional LEO satellites that are left tumbling with uncontrolled attitude.
The purpose of the beacon is to maintain a minimal level of cooperativity after spacecraft failure by transmitting a detectable signal that aids tracking and characterization by relay satellites in Medium Earth Orbit (MEO). In this study, we specifically consider the possibility to reuse the Galileo Search-and-Rescue (SAR) payload as the receiving segment. Residual GNSS reception capability and a low-power transmitter are leveraged to periodically broadcast a beacon message containing the spacecraft identifier and a coarse navigation solution. The primary technical challenge lies in compensating the large, rapidly varying Doppler shifts and Doppler rates resulting from high-velocity orbital motion. Without compensation, these dynamics may prevent the payload, designed for ground user distress signal reception, from reliably acquiring and tracking the distress signal, especially in the likely case of degraded link due to uncontrolled spacecraft attitude and angular motion.
To address this, we propose a two-stage Doppler-compensation architecture that integrates onboard estimation with adaptive signal processing. The first stage implements real-time estimation of dominant Doppler components using GNSS pseudorange and pseudorange-rate measurements. Given the sparsity of measurements due to tumbling motion, the solution incorporates a simplified orbital Extended Kalman Filter (EKF) to provide continuous estimates of the instantaneous line-of-sight (LOS) and relative velocity, compatibly with the limited onboard computational and power resources. The second stage utilizes the EKF outputs to generate transmitter pre-compensation commands—a frequency offset and a time-varying frequency ramp—to counteract predicted Doppler and Doppler-rate effects. These corrections are applied in the beacon’s RF synthesizer and symbol-timing control circuitry.
The paper validates this concept through an end-to-end simulation of realistic LEO failure scenarios using the reference SARGASSIA system configuration for the GNSS receiver and active beacon transmitter. Preliminary results demonstrate the performance benefits of Doppler pre-compensation compared to an uncompensated beacon, highlighting improved acquisition margins. This advantage translates to a higher probability of successful distress signal reception and the partial restoration of cooperation for failed satellites. The analyzed design elements represent a critical milestone for advancing the SARGASSIA project, paving the way for the integration of hardware, receiving and transmitting components. This work explicitly envisions repurposing existing MEO SAR infrastructure to enable a low-cost, low-power solution for maintaining and enhancing SSA capabilities, catalog accuracy, and collision avoidance effectiveness in an increasingly congested LEO environment.