JIHYE PARK, JACLYN J. BOHN, OREGON STATE UNIVERSITY

While the primary purpose of the Global Navigation Satellite System (GNSS) was positioning, navigation and timing (PNT), it has been widely used for environmental monitoring for several decades. As GNSS signals propagate from space to Earth, they interact with various layers of the atmosphere, carrying vital information about the terrestrial environment. In the upper atmosphere, the distribution of electron content in the ionosphere can be measured to observe space weather events [1, 2]or geophysical activities, such as earthquakes and volcanic eruptions that trigger traveling ionospheric disturbances [3-7]. Similarly, signal delays caused by the troposphere provide essential data for monitoring meteorological events [8,9].

Whereas atmospheric effects occur along the direct signal path, environmental sensing at the Earth’s surface is achieved by analyzing “multipath” signals. Traditionally, multipath is considered a critical positioning error to be mitigated. However, these reflected signals contain specific physical information about the reflecting surface itself.

In 1993, Martin-Neira first introduced the concept of using GNSS multipath for environmental sensing—a field now known as GNSS-Reflectometry (GNSS-R). Subsequent research demonstrated the capability of GNSS-R for altimetry; Martin-Neira successfully measured water surface height by computing relative delays between the direct signal and its reflected counterpart [10]. Further geodetic applications were explored by [11], which analyzed the geometry of reflected signals using dual-polarized (right-handed circular polarized, or RHCP, and left-handed circular polarized, or LHCP) antennas.

A more recent and practical evolution of this technology is GNSS-Interferometric Reflectometry (GNSS-IR), introduced by research such as [12] and [13]. Unlike traditional GNSS-R, which requires specialized LHCP antennas to capture reflections, GNSS-IR uses standard RHCP antennas. This technique analyzes the interference pattern created when direct and reflected signals overlap at the antenna. While these interference patterns are present in code pseudorange and carrier phase observations, they are most effectively analyzed through the Signal-to-Noise Ratio (SNR) [12]. 

By modeling the SNR as a function of the satellite elevation angle, researchers can extract the multipath components generated by a planar reflector. Because it uses existing geodetic infrastructure and standard hardware, GNSS-IR offers a powerful and cost-effective method for long-term environmental monitoring, particularly in the study of land-fast ice.

Surface Sensing via SNR 

The primary data source for GNSS-IR is the SNR. In a typical GNSS receiver, the SNR is influenced by signal strength and the antenna gain pattern, which generally increases as a function of the satellite elevation angle. However, the presence of multipath reflections introduces a distinct oscillatory pattern into the SNR data.

By analyzing the frequency of these multipath-driven oscillations, the vertical distance (h) between the antenna’s phase center and the reflecting surface can be determined. According to [12], the frequency of the oscillation (f) remains constant when mapped against the sine of the satellite elevation angle. This relationship is defined by the geometric distance between the antenna and the reflector and the wavelength of the signal (λ): f=2h/λ. Consequently, if the oscillation frequency of the SNR and the specific GNSS wavelength are known, the height of the reflecting surface—such as sea level or ice thickness—can be precisely computed.

Figure 1 illustrates the overall workflow for estimating the vertical distance between an antenna and the reflecting surface by extracting multipath effects from the triple frequency GPS SNR signals, S1, S2 and S5. 

In Figure 1a, the amplitude of SNR increases with the increasing satellite elevation angle, and the presence of oscillation pattern is also seen. To isolate the multipath effect, the trend is removed as shown in Figure 1b, denoted as detrended SNR (dSNR). The representing frequency of this oscillation can be found through a spectral analysis shown in Figure 1c. Each detrended SNR spectra have distinctive dominant frequencies with notable high-power spectrum, which presumably came from a planar reflector causing the multipath. The dominant frequency of each signal is converted to the vertical distance between the antenna and the reflector, that is the height of the surface, h, by taking into account the wavelength of each signal, λ. Consequently, the dominant peaks of three signals are aligned with similar heights as shown in Figure 1d.

While the theoretical framework of GNSS-IR suggests all frequencies should yield identical height measurements for a single reflector, practical observations often reveal slight misalignments, as seen in Figure 1d. This phenomenon arises because different signals—such as GPS L1 (1.575 GHz) and L2 (1.227 GHz)—interact with the reflecting surface differently. Factors like the antenna gain pattern and the surface’s electrical properties create a frequency-dependent scale error [14].

To ensure consistency, many researchers traditionally rely on a single frequency, often favoring GPS L2 because of its higher sensitivity to multipath effects [12]. While this approach provides stable returns, it disregards the redundant information available from modern triple-frequency GNSS signals.

Our research [14, 15] takes a different path by leveraging the full spectrum of available observations (e.g., GPS L1, L2 and L5). We have found that while undetectable biases between frequencies do exist, their magnitude is generally smaller than the inherent observational noise of the GNSS-IR method as [14] reported the scale errors of L1 and L2 as 13 mm and 15 mm, respectively. By analyzing all three signals simultaneously, we can implement a “majority vote” logic to select the most reliable dominant peak. For example, Figure 2 illustrates the spectral power of detrended SNR (dSNR) for GPS L1, L2 and L5. In this instance, L2 and L5 show clear dominant peaks at a height of approximately 7.4 m, while L1 initially shows its strongest spectral power at 7.1 m. By examining the local maxima of the spectrum rather than just the single highest peak, we can identify a secondary peak that aligns with the 7.4 m measurement confirmed by the other two frequencies. This multi-frequency cross-verification significantly reduces the risk of outliers and improves the overall resilience of the monitoring system, especially in complex environments like the frozen Arctic.

A practical consideration in GNSS-IR is that retrieving the reflector height at a specific epoch requires a sufficient duration of time-series observations to characterize the oscillation pattern. This presents a challenge when monitoring dynamic surfaces, such as tidal water levels or moving ice, where the height is constantly changing. To capture this motion while maintaining high-precision results, we apply a sliding window to the dSNR data. This technique limits the observational period of the input signal to a specific temporal “snapshot” that accurately represents the surface height at that moment without sacrificing the frequency of the output.

In [16], we identified an optimal configuration for this sliding window by carefully balancing the sliding interval and the window width. While the interval can be adjusted based on the desired temporal resolution of the final data, the window width requires more precise calibration. It must be sufficiently large to capture the multipath-driven oscillations necessary for spectral analysis, yet narrow enough to prevent the “smearing” of dynamic surface behavior. Ultimately, the proper width is determined by the expected vertical distance between the antenna and the reflecting surface, ensuring the spectral peaks remain sharp even as the environment shifts. More exhaustive details on these parameter selections are provided in [15]. 

Monitoring Land-fast Ice in Alaska

GNSS-IR based tidal monitoring is particularly advantageous in extreme environments such as the Arctic and Antarctica. In these regions, accurate water level observations are vital, yet conventional tide gauges face significant operational hurdles. Because these instruments require direct contact with the water, their installation and maintenance are frequently compromised by harsh conditions and the periodic formation of ice. These limitations were addressed by using data from existing GNSS stations in Alaska to monitor tidal motion [15]. Our study identified and navigated specific high-latitude challenges, including reduced satellite visibility compared to mid-latitude regions and signal quality degradation caused by ionospheric scintillation. Despite these atmospheric and geometric constraints, we confirmed GNSS-IR serves as a robust and valid tide gauge alternative in the Arctic.

Because GNSS-IR measures the characteristics of the reflecting surface, the technique is applicable to monitoring both open water and ice surfaces. In Alaska, land-fast ice forms along the coastlines every autumn and persists until it melts away in the spring. Monitoring this nearshore ice is of critical importance for coastal communities, marine wildlife and regional navigation. Establishing seamless, year-round observations is therefore essential for coastal hazard preparedness and the safety of marine transportation.

To address this need, our research group at Oregon State University (OSU) developed the GNSS-R Water-Ice observation system (GRWIS). The primary objectives of the GRWIS are threefold: to monitor tidal motion regardless of the presence of sea ice, to detect the onset of ice formation, and to assess the dynamic motions of land-fast ice. To validate the system’s performance, a GRWIS station was established in Nome, Alaska (64° 29′ 44.5″ N, 165° 26′ 20.0″ W), operating alongside a traditional tide gauge to provide a direct comparison of the GRWIS solutions.

The GNSS installation in Nome consists of a Septentrio PolaRx5S receiver and a single, upward-facing choke ring antenna mounted on a pier directly overlooking the ocean. This setup is strategically positioned opposite to an operational tide gauge, which is part of the National Oceanic and Atmospheric Administration (NOAA) National Water Level Observation Network (NWLON, Site ID: 9468756). Unlike the GNSS-IR system, which senses the surface remotely, this tide gauge is a contact-based sensor that is heated and structurally protected from the extreme open-ocean conditions of the Arctic. This specialized protection ensures a continuous record of water level estimations throughout the year, providing a reliable and high-fidelity benchmark against which the GRWIS solutions can be validated across both open-water and ice-covered periods.

Water Level Estimation Using GRWIS in Nome

The experimental results from the Nome station demonstrate that GNSS-IR remains highly effective for water level estimation even under the rigorous constraints of high-latitude environments. While data acquisition and processing in these regions are often complicated by limited satellite geometry, ionospheric scintillation and extreme weather, our analysis showed strong agreement with the NWLON benchmark. Figure 4 illustrates a comparison between the GRWIS-derived water levels and the NOAA tide gauge during an ice-free period from November 2 to 8, 2023.

In the upper plot of Figure 4, the GNSS-IR based estimations (depicted in blue) closely track the ground-truth water levels provided by the NWLON tide gauge (depicted in grey). The lower plot quantifies the precision of the system, presenting the discrepancy between the two datasets. The residuals vary within a narrow range of approximately -5 cm to +5 cm, confirming the GRWIS system can achieve geodetic-grade accuracy for tidal monitoring despite the technical challenges inherent to the Arctic.

Sea Ice Detection

Monitoring sea ice using ground-based GNSS-IR is an emerging area of research, building on established principles of signal coherence and surface roughness. Early investigations by [17] in Disko Bay, Greenland, demonstrated a clear relationship between the number of coherent reflected signal observations and the presence of sea ice. This supported the earlier theoretical framework by [18], which posited that increased surface roughness on the open ocean significantly influences GNSS-R signal coherence. To quantify this, [19] introduced a damping coefficient derived from the attenuation of dSNR time series. While this coefficient includes unmodeled elevation-dependent effects, it serves as a proxy for reflector height variance and the physical state of the surface. More recently, [20] used GNSS interference frequencies to monitor sea ice in Finland. They noted that during frozen periods, the discrepancy between GNSS-IR height and mean sea level corresponds to the “total freeboard” (ice plus snow accumulation), which can be converted into ice thickness via hydrostatic balance equations.

Our research group at OSU has advanced these methods by introducing a numerical indicator called the Confidence Level of Retrieval (CLR). The CLR is the ratio between the amplitude of the dominant spectral peak and the average amplitude of the remaining peaks in the SNR spectrum. It provides an intuitive measure of how clearly a single reflecting surface—such as calm water or flat ice—stands out against background noise or surface scattering.

As illustrated in Figure 5, the spectral domain changes significantly based on surface conditions. In calm conditions (a), the dominant peak is sharp and unmistakable, resulting in a high CLR. Under rough conditions (b), the spectral power is distributed across multiple peaks (marked with “X”), lowering the relative strength of the dominant peak. We have found the CLR performs comparably to the damping coefficient used by [21] for monitoring wave heights, suggesting the CLR is a robust tool for characterizing the transition from turbulent open water to stable ice.

A year-long analysis of CLR data from Nome (November 1, 2023, to October 31, 2024) reveals a distinct seasonal signature that aligns with the formation and retreat of land-fast ice. During the ice-free period from November to early December, the moving average CLR remains relatively low at approximately 17 ± 9. Occasional dips below a value of 5 in this period correspond to rough sea states and high wave action. However, as land-fast ice stabilizes in mid-December, the CLR shifts dramatically, increasing to an average of 38 ±7. This high-confidence state persists until June 2024, when the spring melt commences and the CLR returns to its baseline ice-free average of 14 ± 9. This clear threshold behavior confirms the CLR is a highly effective metric for the automated detection of sea ice presence.

Spectral Analysis Using Continuous Wavelet Transform

To further analyze the complex frequency components of the GNSS-IR data, we employed the Continuous Wavelet Transform (CWT). Unlike the standard Fourier Transform or the Lomb-Scargle Periodogram, which decompose a signal into infinite sine waves and lose temporal localization, the CWT uses shifted and scaled versions of an original “wavelet”—an asymmetric, wave-like oscillation that begins and ends at zero [22]. This allows for the simultaneous extraction of instantaneous frequencies and their corresponding amplitudes over time, providing a clear advantage for monitoring non-stationary signals like those found in dynamic Arctic environments.

Our study specifically focused on data from April 2024, a period characterized by the simultaneous presence of sea ice and snow cover. Using estimation techniques, we compared GNSS-IR height measurements to the NOAA tide gauge benchmark after removing outliers exceeding three standard deviations (Figure 7a). A persistent offset was observed between the two datasets, largely attributable to snow accumulation on the land-fast ice. Because GNSS-IR signals reflect off the uppermost surface—in this case, the snow—the measurement represents the combined height of the water, ice and snow. In contrast, the heated, sheltered tide gauge measures the water level exclusively. By subtracting the tide gauge data from the GNSS-IR observations (Figure 7b), we effectively isolated the “deviation” signal, removing the dominant tidal motion to focus on higher-frequency surface dynamics. 

The CWT output is visualized as a magnitude scalogram, where the x-axis represents time, the y-axis represents frequency, and the color intensity indicates the strength of the correlation between the signal and the wavelet. Within these scalograms, the Cone of Influence (COI)—indicated by dashed lines—marks the boundary where edge effects from the wavelet transform become significant. Data within the COI provides an accurate time-frequency representation, while results outside it are potentially influenced by the finite length of the time series.

Analyzing the scalograms in Figure 8 reveals distinct differences. The tide gauge scalogram shows almost no high-magnitude regions at higher frequencies, consistent with a sensor protected from surface noise, while the GNSS-IR scalogram displays numerous high-magnitude “bright spots” at high frequencies. While some of this is inherent noise from multiple reflection points within the Fresnel zone, these signatures also capture non-tidal surface movements. By removing the low-frequency semidiurnal tidal components shown in Figure 8c, the remaining high-frequency signatures are isolated. While some outliers remain, these scalograms confirm GNSS-IR is capturing surface reflections beyond simple tidal oscillations.

Through visual inspection of the scalograms, we identified a dominant energy band between approximately 2.0×10^-5 Hz and 2.6×10^-5 Hz. Using a bandpass filter, this region of the plot is isolated between 1.8×10^-5 Hz and 2.8×10^-5 Hz to calculate the period. The dominant period for the GNSS-IR data is 12.06 hours, and for the tide gauge data it is 12.83 hours, both of which align closely with the expected ~12-hour cycle of semidiurnal tides. 

To isolate this tidal motion from the GNSS-IR data, we low-pass filtered at 2.6×10^-5 Hz. After filtering, the majority of high-magnitude values at high frequencies are removed (Figure 9a). The low-pass filtered GNSS-IR water levels follow the tidal motion (Figure 9b). As shown in Figure 9, this filtering effectively removed the high-frequency magnitude peaks, resulting in a smoothed GNSS-IR water level time series that closely follows the tidal benchmark while maintaining the seasonal surface offset.

Detecting Snow Accumulation

Once land-fast ice is established, the reflecting surface effectively becomes a multi-layer system consisting of water, ice and accumulating snow. Because the GNSS-IR antenna captures reflections from the uppermost interface, its height measurements incorporate the total thickness of the snow and ice layers. In contrast, the heated and sheltered NOAA tide gauge continues to measure the water level exclusively. This disparity provides a unique opportunity to isolate snow depth by comparing the two datasets.

Figure 10a displays the low-pass filtered GNSS-IR water levels alongside the tide gauge data during the fieldwork period of April 3 to 7, 2024. At the beginning of this interval, the discrepancy between the sensors is near zero; however, the offset increases and fluctuates as the fieldwork progresses. We evaluated this difference by applying a six hour moving average to suppress uncharacterized high-frequency oscillations, revealing a clear trend in the surface elevation.

To validate whether this offset truly represents snow accumulation, we compared the GNSS-derived difference against in situ data from three snow surveys conducted during the fieldwork (Figure 10b). The GNSS-IR results summarized in Table 1 show reasonable agreement with the average snow depth and standard deviation from these physical surveys, supporting the hypothesis that the measurement offset is a direct proxy for snow depth.

Summary and Future Work

This study demonstrates that GNSS-IR is a versatile and robust tool for monitoring the Arctic’s complex, multi-layered environments. By using the GRWIS system in Nome, Alaska, we successfully established a method for independently estimating tidal motion, snow accumulation, and the dynamic signatures of land-fast ice from a single geodetic-grade receiver.

Our application of CWT proved instrumental in identifying the distinct frequency components within the reflected signals. By establishing precise cutoff frequencies, we were able to effectively low-pass filter the GNSS-IR data, isolating the semidiurnal tidal cycles from high-frequency surface noise. A key finding of this work is the characterization of the vertical offset between the remote GNSS-IR measurements and contact-based tide gauge data. By correlating these offsets with in-situ measurements, we have shown this discrepancy serves as a reliable proxy for snow depth, effectively turning a measurement “error” into a valuable environmental metric.

While the results are promising, the current validation of the snow-depth estimation is constrained by the relatively short duration of the April 2024 field campaign. A limited observational window for ground-truth data inherently restricts our ability to characterize the system’s performance across the full spectrum of Arctic weather events, such as heavy storm surges or rapid mid-winter melt-refreeze cycles.

Moving forward, we intend to expand our research to more precisely identify the specific spectral frequencies that correspond to snow depth and ice deformation. Future work will involve longer-term validation campaigns and the development of automated algorithms to separate snow accumulation from ice-loading events. By refining these multi-frequency GNSS-IR techniques, we aim to provide coastal Arctic communities with a maintenance-free, year-round solution for monitoring the increasingly unpredictable dynamics of land-fast ice. 

Acknowledgment

The authors gratefully acknowledge the National Science Foundation (NSF) for its support of this research through the Arctic Observational Network (AON) EAGER grant #2321313. We also extend our gratitude to the local community in Nome, Alaska, and the NOAA Integrated Ocean Observing System (IOOS) for providing the critical benchmark data used in this study.

References 

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Authors

Dr. Jihye Park is an associate professor of Geomatics in the School of Civil and Construction Engineering at Oregon State University (OSU). Before joining OSU, she worked as a post-doctoral researcher in Nottingham Geospatial Institute at University of Nottingham, UK. She holds a PhD in Geodetic science and surveying at The Ohio State University. Her research interests include GNSS positioning and navigation, Precise Point Positioning, Network Real-time kinematic, GNSS meteorology, GNSS-Reflectometry, and GNSS remote sensing for monitoring the earth environments, natural hazards, as well as artificial events.

Jaclyn Bohn is a graduate student at Oregon State University in the School of Civil and Construction Engineering studying geomatics. She received her bachelor’s degree in mathematics from the University of Utah. Her research interests lie in applications of GNSS-Reflectometry to monitor coastal areas.

The post Signals from the Ice appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

The HydroGNSS mission—ESA’s first Earth Observation “Scout” mission to reach orbit—launched from Vandenberg Space Force Base in California in November 2025 and consists of two small satellites designed to monitor key hydrological and climate variables using signals from global navigation satellite systems (GNSS). 

EECL supplied six multiband ultra-low-noise microwave amplifiers (LNAs) that form part of the radio-frequency front end for the mission’s GNSS reflectometry receiver. The LNAs amplify extremely weak reflected navigation signals while preserving signal integrity, allowing the satellites to capture usable data at the earliest stage of signal reception. 

HydroGNSS uses a technique known as GNSS reflectometry, in which satellites receive navigation signals from systems such as GPS and Galileo after they bounce off Earth’s surface. By analyzing those reflections, the spacecraft can derive environmental measurements including soil moisture, freeze–thaw conditions over permafrost, inundation and wetlands, and above-ground biomass. 

Early commissioning results indicate the payload hardware is performing as expected. Both satellites have successfully begun collecting Delay Doppler Maps—datasets that characterize the reflected GNSS signals and allow scientists to extract environmental information about the reflecting surface. 

The LNAs were designed, manufactured and tested in the United Kingdom under a contract with Surrey Satellite Technology Ltd. (SSTL), which built the satellites and the GNSS receiver payloads. Their in-orbit performance validates the RF hardware after several years of development and space-qualification testing. 

Low-noise amplification is particularly critical for GNSS reflectometry missions because the reflected navigation signals arriving at the satellite are extremely faint compared with direct signals from the GNSS satellites themselves. Maintaining a very low noise figure in the front-end electronics enables the receiver to detect these weak reflections and generate usable scientific data products. 

HydroGNSS will collect global measurements of hydrological conditions to support climate monitoring and environmental research. According to ESA, the twin satellites operate in complementary orbital positions to maximize global coverage while continuously gathering reflected GNSS signals for analysis.

The post EECL Amplifiers Reach In-Orbit Milestone on ESA HydroGNSS Mission appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

Over the last several days, maritime analytics providers have documented interference events affecting more than 1,000 ships in the Middle East Gulf, alongside a growing pattern of AIS anomalies and “dark” operations. At the same time, tanker and container traffic has slowed or stopped near the Strait of Hormuz, and leading war-risk insurers are withdrawing cover for the region. 

The episode illustrates in practical terms what a contested RF environment means for ships that still rely heavily on satellite-derived position for navigation, tracking and compliance.

Interference profile: GPS jamming and AIS spoofing on a regional scale

Maritime intelligence firm Windward reports that more than 1,100 vessels experienced GPS and AIS interference across the Middle East Gulf within a single 24-hour period following the outbreak of hostilities between Iran, the United States and Israel. Ships’ reported positions were displaced onto airports, inland locations in Iran and the Gulf states, and even over a nuclear power plant, producing track histories that are clearly inconsistent with physical reality. 

A parallel assessment reported by Wired, based on analysis of satellite navigation attacks since the start of the air campaign against Iran, arrives at a similar figure of roughly 1,100 ships affected, underscoring that interference is not limited to a small subset of vessels or a single narrow area. 

Dryad Global notes “heightened risk of GPS jamming and AIS spoofing” in the Gulf of Oman and Strait of Hormuz, explicitly linking recent anomalies to Iranian naval exercises and electronic warfare activity. 

Taken together, the data suggests:

• GNSS-derived position can become systematically biased over wide areas, not only momentarily lost.
• AIS tracks based on those positions may show vessels apparently transiting over land, clustered around inland targets, or moving in circular or jagged patterns that reflect repeated loss and reacquisition of signal.
• Some operators respond by switching AIS off altogether, which protects them from misinterpretation of spoofed positions but reduces visibility for collision-avoidance and traffic management.

From a PNT standpoint, this is a textbook case of how GNSS jamming and spoofing propagate through downstream systems that treat satellite position as authoritative.

Shipping, insurance and security advisories

The interference is occurring against the backdrop of a broader shipping disruption centered on the Strait of Hormuz.

Reuters reports that around 150 ships, including oil and LNG tankers, are currently stranded near the Strait of Hormuz, with at least five tankers damaged and crew casualties following drone and missile attacks. In the wake of US and Israeli strikes, Iran has announced that it is closing the strait, and many market participants now characterize conditions as a “de facto” closure of a route that normally carries about one-fifth of global oil exports and substantial volumes of gas.

In response to the increased risk:

• Major war-risk underwriters, including Gard, Skuld, NorthStandard, the American Club and others, are cancelling war-risk cover for ships operating in Gulf and Iranian waters from early March, with premiums for any residual cover rising sharply. 
• Container carriers such as Maersk and CMA CGM have begun rerouting or suspending services that would normally pass through Hormuz, adding to the reduction in commercial traffic through the area. 

On the governmental side, a recent advisory from the US Maritime Administration designates the Strait of Hormuz, Persian Gulf, Gulf of Oman and parts of the Arabian Sea as an area of active military operations and potential retaliatory strikes by Iranian forces. The advisory highlights the risk of hailing, boarding or detention of commercial vessels and directs operators to closely monitor updates and guidance from US Naval Forces Central Command. 

Although these notices are primarily focused on kinetic threats, several security circulars from P&I clubs and risk advisers now explicitly call out the likelihood of GPS interference and AIS anomalies in the region and recommend that ships treat GNSS-based position with caution when operating there. 

Implications for PNT resilience

The current pattern of events around Hormuz reinforces several points that have been discussed in standards bodies and industry forums for some time:

• GNSS reliability is not uniform. In certain strategic waterways, including parts of the Gulf and Strait of Hormuz, interference can reach a level where satellite-based positioning should be treated as advisory rather than authoritative. 
• Spoofed or displaced positions can have regulatory and commercial consequences, not just navigational ones, when automated compliance systems interpret false AIS tracks as evidence of port calls or territorial incursions. 
• “Going dark” on AIS reduces exposure to mis-located tracks but increases dependence on radar and visual watchkeeping, especially in confined waters.

For PNT system designers and policy-makers, the current situation underscores the value of alternative and complementary positioning sources, whether that means terrestrial systems, inertial aids, or hardened multi-constellation receivers, and the need to assume that in some regions, GNSS degradation will not be an exception but a recurring operating condition.

In that sense, the developments around Hormuz are less an isolated crisis than another data point in an evolving pattern: satellite navigation has become a routine instrument in regional competition, and maritime navigation practices are having to adjust accordingly.

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Supported by the European Space Agency (ESA), the RIPTIDE Phase 2 project has field-tested an integrated ‘Monitor & Protect’ demonstrator tailored to operations in the Black Sea and Lower Danube Basin.

Led by GMV Innovating Solutions Romania, with the Romanian Space Agency Research Centre and the Romanian Maritime Hydrographic Directorate, the project addressed jamming and spoofing risks affecting ports, shipping lanes and coastal infrastructure. The goal was to design, implement and validate an alternative PNT capability that complements GNSS.

RIPTIDE Phase 2 implements a demonstrator that integrates GNSS monitoring, trusted or verified navigation messages distributed via AIS/VDES ASM, and VDES-R/R-Mode ranging. At the authority level, coastal interference monitoring is combined with VDES transmitters that provide alternative ranging signals and trusted navigation data. At the vessel level, multi-constellation GNSS is augmented by VDES-R positioning and onboard interference detection, enabling autonomous operation when GNSS is degraded.

Targets achieved

Project results were presented at a recent ESA-hosted event by Florin Mistrapau, Vladimir Kosjer and Calin Ciobanu of GMV Romania, together with Petrica Popov of the Romanian Maritime Hydrographic Directorate and Irina Stefanescu of the Romanian Space Agency Research Center.

Partners undertook requirements engineering, system architecture definition, laboratory integration and Black Sea trials. A core element is the Monitor & Protect workflow, which cross-checks GNSS interference indicators, navigation message integrity and PVT consistency. When anomalies are detected, the system switches to VDES-R positioning, maintaining continuity of service.

Live trials aboard MHD’s Ocean 2 research vessel confirmed resilience under real GNSS jamming and spoofing conditions. VDES-R/R-Mode delivered position errors below 10 metres during strong interference, while Monitor & Protect cross-checks detected spoofed and degraded GNSS scenarios. Performance was further validated through emulated localized degradation and coordinated attack campaigns using Skydel-based spoofing, achieving technology readiness level (TRL) 6.

Analysis also revealed correlation between carrier-to-noise density, pseudorange quality and VDES-R positioning accuracy. Beyond maritime navigation, the consortium identified a list of potential applications including search and rescue, emergency management, aviation and drones, and road and rail transport.

Funded under ESA’s NAVISP program, RIPTIDE Phase 2 shows how combining alternative ranging, trusted data distribution and intelligent monitoring enhances maritime resilience, offering a blueprint for hybrid PNT systems capable of maintaining safe navigation during GNSS interference.

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GNSS Interference as a Trigger

Specifically mentioned is Russia’s regular disruption of GNSS signals in the region and its negative impacts on maritime safety. The letter was posted on government sites the same day as the release of a major report by the United Kingdom’s Royal Institute of Navigation about the adverse effects of GNSS interference on maritime operations.

The declaration seems to indicate a seismic shift in how these nations regard and enforce international maritime codes. Heretofore vessels in “innocent passage” were rarely interfered with, even if there were suspected violations. 

The letter and its enforcement also may be a way to finally bring a halt to Russia’s unabashed jamming and spoofing of GPS and other GNSS signals in the region.

The letter opens by citing maritime’s dependence on GNSS, the hazards of it being disrupted, and places the blame for recent disruptions squarely with the Russian Federation. 

It then calls on all nations and maritime operators to recognize that interference with GNSS and shipboard AIS systems is a safety and security threat, and to train mariners to operate safely when GNSS is not available.

It also calls for the international community and nations to “Cooperate on the development of alternative terrestrial radionavigation systems which may be used in place of GNSS in the event of disruption, loss of signal or interference.” 

Alternative Terrestrial Radionavigation and MaRINav

The Maritime Resilience and Integrity of Navigation (MaRINav) project was sponsored by the European Space Agency and examined several terrestrial and space-based systems. The project’s report published in 2020. Since then, several nations in northern Europe have begun or completed projects to improve one or more aspects of positioning, navigation, and timing. These include terrestrial-based timing systems in Finland, Sweden, Norway, and the United Kingdom (UK), and the UK and France agreeing to establish an eLoran network. 

A Manifesto for Stricter Enforcement

The open letter seems to be very much a manifesto and is addressed to all organizations and individuals involved in maritime operations from the U.N.’s International Maritime Organization, to nation-states, shipping companies, and individual seafarers.

After its discussion of protecting GNSS and AIS, the letter goes on to say that all international maritime law and norms must be more strictly adhered to.

“Furthermore…the full and consistent implementation of the International Maritime Organization (IMO) regulations is fundamental to ensuring maritime safety, the smooth functioning of shipping, and the protection of seafarers and the marine environment…”

The increasing use of “shadow fleets” to avoid international sanctions is specifically mentioned. 

The signatories say they “require” compliance and use “shall“ and “must” when referring to adherence to specific provisions. 

“[We] require that all vessels exercising freedom of navigation strictly comply with applicable international law, whether customary international law or as contracting parties to international conventions…”

Such language seems to indicate a willingness, perhaps even an eagerness to take enforcement action against offenders.

Stateless Vessels and Shadow Fleets

Ten frequently violated provisions of the Safety of Life at Sea Convention and other international maritime agreements are mentioned as concerns. They include precautions to avoid collisions, to ensure vessels have proper documentation, and to prevent pollution.

The first to be mentioned is the requirement that a ship fly the flag of only one nation-state. Ships that fly the flags of two or more states are deemed stateless. A vessel is also deemed stateless if it is flying a nation’s flag, but that nation does not acknowledge it is one of theirs. Any nation can take law enforcement action against stateless vessels much like they would against pirates.

Where Enforcement Might Bite

How and where the signatories will act against violators is not mentioned in the letter. This is the real “meat” of the issue and will determine how much of a sea change this will be. Presumably, they will focus on shadow fleet vessels that can be treated as stateless. 

Conceivably they could act against at least some violations anywhere on the globe outside of the territorial waters of another nation. 

It is most likely that, at least initially, enforcement will be focused on the Baltic and North Sea. Both of these areas, with the exception of a small portion of the Gulf of Finland near St. Petersburg, Russia, lie within the Exclusive Economic Zones (EEZ) of one of the letter’s signatories. Under the U.N. Convention of the Law of the Sea (UNCLOS), coastal states have the ability to enforce regulations to protect their waters in these zones. An EEZ typically extends 200 nautical miles seaward, or until it meets the EEZ of another nation. 

Leverage Over Russian Trade Routes

In addition to making maritime generally safer, the declaration and its follow-on actions could be an effective way to greatly curtail or halt Russian interference with GNSS in the region. 

All traffic to Russian ports in Kaliningrad and St. Petersburg must make lengthy transits through the North Sea and Baltic. This commerce, especially through St. Petersburg, is critical as it serves a large segment of Russia’s industry and population. Any slowing or reduction could have significant economic consequences. 

The letter was signed by “The Coastal States of the Baltic Sea and the North Sea with Iceland: Belgium, Denmark, Estonia, Finland, France, Germany, Iceland, Latvia, Lithuania, the Netherlands, Norway, Poland, Sweden, and the United Kingdom.”

The open letter is available on numerous government websites such as the German Federal Ministry of Transport.

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This Belgian Defense-commissioned research program is aimed at enabling fully autonomous unmanned aerial system (UAS) approach and landing on moving vessels under conditions where conventional satellite navigation can be unreliable or unavailable.

As 2026 begins, heightened GNSS vulnerability concerns make Agilica’s hybrid PNT work very pertinent. The company’s ground-based localization (AGL) positioning system is an alternative PNT solution that blends ultra-wideband (UWB) terrestrial signals with seamless GNSS integration, including the Galileo High Accuracy Service, to extend precision navigation into GNSS-challenged environments.

The underlying architecture operates much like a terrestrial ‘mini constellation’; fixed UWB anchors with known coordinates broadcast ranging signals to mobile tags on UAVs, enabling centimeter-level positioning accuracy even during multipath or signal obstruction that would typically plague GNSS alone.

This hybrid approach was validated earlier in 2025 when Agilica successfully completed a European Space Agency (ESA)-funded feasibility study that confirmed the technical and commercial viability of the AGL system for precision navigation and landing tasks in unfavorable environments, including indoor spaces, offshore platforms and moving vessels at sea. The study demonstrated the system’s ability to augment GNSS with UWB-based local positioning and achieve sub-20 cm accuracy.

High-level coordinated effort

SAILS, funded under the Belgian Defense DEFRA program, with a €1.6 M budget and running from 2025 through 2028, brings together Sabena Engineering, the Belgian Navy, the Royal Military Academy, and Agilica. The consortium aims not just to enable autonomous drone landing but to extend UAV operational envelopes in high seas, harsh weather, and GNSS-challenged environments, essential for military, offshore energy, and search-and-rescue missions.

“Landing a drone on a moving ship is among the toughest navigation challenges in maritime autonomy,” Bart Scheers, COO of Agilica, told the press in late 2025. “With SAILS, we’re moving from concept to operational demonstration, bridging maritime robotics and safe flight operations.”

As GNSS vulnerabilities, from interference to signal blockage, increasingly constrain autonomous systems, Agilica’s work reflects a broader shift toward resilient PNT architectures. By combining multi-sensor fusion with terrestrial augmentation, the SAILS project demonstrates how GNSS-centric autonomy can be strengthened for operations in environments where satellite navigation alone cannot meet performance or integrity demands.

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Reporting from BBC Verify (Joshua Cheetham, Paul Brown, Richard Irvine-Brown & Matt Murphy) demonstrates how the Skipper, long sanctioned under its former identity Adisa, systematically falsified its UN-mandated Automatic Identification System (AIS) broadcasts while shuttling crude oil between Iran, Venezuela, and China.

AIS is intended to provide continuous vessel location and identity data. Yet, as analysts at Kpler told the BBC, the Skipper repeatedly transmitted positions placing it at Iraq’s Basrah Oil Terminal even as terminal logs showed no trace of the ship. Satellite imagery and independent confirmation from TankerTrackers.com later placed the vessel at Iran’s Kharg Island during the same period.

The Skipper‘s disappearance from public tracking feeds between 7 November and 10 December, during which imagery confirmed its presence at Venezuela’s Port of Jose, further illustrates how spoofed or suppressed GNSS data facilitates covert loading operations. By 16 November, Kpler estimated the tanker had taken on at least 1.1 million barrels of Merey crude, later conducting additional ship-to-ship transfers off Barcelona, Venezuela.

Belgian naval analyst Frederik Van Lokeren told BBC Verify that such transfers, while not explicitly illegal, remain “extremely uncommon” for legitimate tankers, and usually indicate an effort to evade sanctions.

Timely input

It is apt to include a European voice here; over the past two years, the continent has faced persistent GNSS jamming and spoofing incidents from the Baltic to the Eastern Mediterranean, affecting commercial aviation and maritime operations.

The European Union Aviation Safety Agency (EASA) and several national regulators have warned that state-sponsored interference has grown more frequent and more tactical, highlighting vulnerabilities that mirror those exploited by the Skipper in contested maritime zones.

In this context, the Skipper seizure is not an isolated incident but part of a broader signal-integrity crisis. Whether in European airspace or in Venezuela’s offshore loading corridors, authorities now face adversaries capable of manipulating GNSS-dependent systems with impunity.

For the maritime sector, where AIS spoofing has become a hallmark of opaque, sanctions-busting operations, the episode underscores the urgent need for resilient positioning, authentication, and cross-sensor verification. Without such measures, the dark fleet will continue to navigate invisibly, even as its shadows extend across continents.

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Without reliable, high-accuracy positioning and attitude determination, autonomous ships risk making navigation errors that can result in inefficient maneuvers, and even collisions or groundings. Addressing this challenge, MAPP project partners developed a new platform that enhances navigation safety and reliability in port environments, marking a major step toward fully autonomous maritime operations.

MAPP integrates a sophisticated sensor suite comprising GNSS, IMUs, stereo cameras, and a solid-state LiDAR, all managed through a modular hardware and software architecture. The system combines GNSS-PPP and RTK correction solutions with visual and LiDAR-based localization, fusing data through extended Kalman and particle filters to ensure consistent positioning and attitude determination.

This multi-layered approach, featuring a model-based hybrid state space (MHSS) integrity monitoring scheme, enables real-time fault detection and exclusion, ensuring reliable navigation data even in complex and GNSS-challenged port conditions.

Exemplary R&D

At a recent ESA-funded event, Shashank Govindaraj and Jitao Zheng of Space Applications Services, together with Jorge Moran Garcia, Jan Fischer, and Sai Parimi of ANavS, presented the final results of the MAPP project.

Field trials conducted in Trieste and Palma de Mallorca validated the platform’s performance in three key use cases: port approach, port navigation, and docking. Results showed sub-meter positioning accuracy and heading errors below one degree, meeting stringent key performance indicators for maritime operations.

The system maintained 100% availability in port approach and in-port navigation scenarios, with protection levels consistently overbounding position errors. While the docking phase’s 25 cm horizontal alert limit was not fully achieved, the team identified that relative positioning techniques could enhance future performance.

A highlight of MAPP is its robustness against sensor failures. The central fusion filter maintained stability during GNSS outages and sensor dropouts, with minimal drift thanks to integrated inertial and visual data. Fault detection mechanisms successfully identified and mitigated a wide range of simulated errors without degrading accuracy.

Moving forward, Govindaraj said, MAPP partners will work to increase system maturity through testing on larger vessels and preliminary integration into ship navigation systems, paving the way for safer and smarter autonomous maritime navigation. This activity was fully funded under NAVISP Element 1, which aims to boost European innovation in Positioning, Navigation and Timing (PNT).

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Testbed submarine XV Excalibur went to sea with Infleqtion’s quantum optical atomic clock on board – the first time such a device has been operated at sea in an underwater vessel.

The successful trial, which saw the Royal Navy work hand-in-hand with the Submarine Delivery Agency’s Autonomy Unit team, saw Infleqtion’s Tiqker clock demonstrate precision timing onboard the extra-large uncrewed underwater vessel (manufactured by MSubs) which has been undergoing various sea trials.

Unlike other vessels, submarines cannot rely entirely on GPS for navigation and traditional microwave-based clocks provide stability but can drift over time – making them less accurate.

The use of quantum technology in systems like Tiqker add to a submarine’s ability to maintain accurate timing and navigation and reduce the need for external signals. These advantages allow the submarine to stay submerged and covert for longer.

Commodore Marcus Rose, Deputy Director Underwater Battlespace Capability within the Royal Navy’s Develop Directorate, said: “This trial is a significant milestone in the development of Extra Large UUV capabilities in the Royal Navy. 

“It demonstrates the ability to rapidly develop and integrate payloads into uncrewed host platforms, which is essential for ensuring the Royal Navy can respond to, and get ahead of, adversary capabilities.” 

Commander Matthew Steele, Head of Futures in the Royal Navy’s Disruptive Capabilities and Technologies Office, added: “I am delighted that our long-term collaborator Infleqtion was able to test its quantum atomic clock onboard Excalibur.  

“This experiment was a first critical step towards understanding how quantum clocks can be deployed on underwater platforms to enable precision navigation and timing (PNT) in support of prolonged operations.  

“The DCTO looks forwards to championing further trials of quantum-based navigation technologies, such as Tiqker, onboard Excalibur as we seek to deliver quantum operational advantage for the Royal Navy.”

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Developed by Romanian InSpace Engineering (RISE) in collaboration with the Maritime Hydrographic Directorate (MHD), and funded by the European Space Agency NAVISP Element 2, the system addresses key maritime navigation issues such as multipath errors, interference, and limited ground truth accuracy.

The concept builds on expertise gained from previous ESA projects, including extensive data collection campaigns in the Black Sea, the Aegean Sea, and along the Danube River. These operations involved both piggyback and dedicated vessel deployments, with GNSS data collected and analyzed for performance assessment, interference detection, and multipath characterization.

At a recent ESA-hosted event, Sergiu-Stefan Mihai and Ileana Mihu of RISE presented the final results of the project. At the core of NEURONAV is a machine learning model, Mihai said. Specifically, a convolutional neural network (CNN) is trained to predict and correct position errors caused by multipath.

Unique data processing

The system first gathers GNSS-derived parameters such as satellite azimuth, elevation, carrier-to-noise density ratio (C/N₀), and pseudorange residuals. These inputs are transformed into a Cartesian error space representation, which serves as the CNN’s input matrix. The network processes this data through convolutional layers, max pooling, and fully connected regression layers to predict position corrections in X, Y, and Z coordinates.

NEURONAV hardware features an integrated Septentrio mosaic-X5 multi-constellation, multi-frequency GNSS receiver, with a Jetson Nano single-board computer for AI computation. Data acquisition, processing, and storage are automated, enabling continuous model training and validation without human intervention.

Testing campaigns using MHD’s hydrographic vessels in the Black Sea demonstrated consistent results across multiple trials. Even under heavy radio frequency interference, in line with the observed regional uptick in GNSS jamming and spoofing since the start of the conflict in Ukraine, the trial results demonstrated measurable accuracy gains. For example, in one validation run, mean position error dropped from 1.507 m with the raw receiver output to 1.268 m with NEURONAV corrections. The 95th percentile error improved by over 25 percent compared to the uncorrected GNSS data.

With its ability to augment existing GNSS receivers and process data locally for security and resilience, NEURONAV offers potential benefits for users in both professional and recreational maritime sectors. Mihai said future work will focus on improving performance under severe interference, expanding datasets, and integrating additional navigation sensors for enhanced robustness.

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