United Kingdom

Ships nowadays greatly rely on Global Navigation Satellite Systems (GNSSs) in order to determine their position.
Since GNSS outages or jamming events do occur, there are efforts to reduce the dependency on GNSS for maritime Navigation.
One such effort is called R-Mode (Ranging Mode), and focuses on complementing maritime communication systems by
a ranging component to determine the position on the vessel. One of the systems to be extended by R-Mode is the VHF Data Exchange System (VDES).
The VDES communication system is currently in standardization and offers 100 kHz of bandwidth in the maritime VHF band. It utilizes single carrier modulation with π/4-QPSK.
The proposed R-Mode extension works by sending a precisely timed known data sequence, so that time of arrival estimation allows determination of the range.
Using software defined radios (SDR), we implemented a test setup for VDES R-Mode with three base stations and one receiver.
Using this setup, we performed the first VDES R-Mode positioning trials on the Lake Ammer in Germany using different ranging sequences.
By determining the time of the arrival as well as the Doppler shift of the received signals we tracked the boat’s position with an Unscented Kalman Filter.
The positioning accuracy performance ranged to up to 10 meter under favourable conditions.
Crucial was the consideration of the Doppler measurements to enhance tracking performance considerably.

Navigation 2021

On the Positioning Performance of VDES R-Mode

### Welcome to Navigation 2021!

Our aim was to bring diverse disciplines together to stimulate insights and knowledge sharing towards a more navigable world. We hope we achieved this!

Navigation and timing are critical to the world we all inhabit. We believe that the work of the wider navigation community enables societal benefit including support to national grand challenges and also the United Nations’ Sustainable Development Goals. To achieve this requires collaboration and understanding across science, technology and practice.

Navigation 2021 is about much more than technology innovation, it also showcases science and research from across the wider community, including animal navigation, cognition and human factors.


Our aim was to bring diverse disciplines together to stimulate insights and knowledge sharing towards a more navigable world. We hope we achieved this!

technical paper

Session 1.3.

Monitoring GNSS and detecting threats to it are crucial to the better understanding of the scale and risk posed to GNSS end users by PNT disruption, and therefore to being able to counter the threat. Under the GNSS Event Notification Service (GENS) project, CGI has developed scalable and effective tools that fuse multiple data sources to enable live situation awareness of GNSS spectrum quality as well as long term trend analysis. In this process, CGI has integrated its PNT Incident Event Monitoring (PNTIEM) system with existing UK-developed sensors from Ordnance Survey’s (OS) OS NET network of GNSS receivers and GMV NSL’s DETECTOR and Strike 3 interface technologies.

In this talk, CGI will present a summary of the project achievements, how it has brought together its Navigation and Spectrum domain expertise and its scaled agile and SecDevOps delivery experience to create the foundations of a national GNSS event monitoring and incident management capability for the UK. The talk will include key points fed into the project technical direction through the stakeholder engagement, as well as presenting an overview of the system, its innovative aspects such as the data fusion approach, and some of the surprising headline themes that emerged from the observed results. The talk will conclude by covering the recommended next steps for follow-on work.

Status Update on the UK NAVISP GENS project (GNSS Event Notification Service

Adaptive notch filters (ANFs) have shown good interference mitigation capabilities against chirp interferences. However, the chirp dynamics and jump discontinuities in frequency limit ideal ANF tuning for all chirp types. An ANF removes a spectrally sparse interference through a notch filter, and an adaptive algorithm determines the center frequency of the chirp as it changes over time. One adaptive algorithm approach uses a conventional frequency-locked loop (FLL) with fixed settings to follow the chirp frequency. A critical tuning parameter of the FLL is the loop-bandwidth, which is a trade-off between the agility and noise suppression of the FLL. On the one hand, large bandwidth adapts quickly and is suitable for addressing the chirp’s jump-discontinuities but results in noisy estimates. On the other hand, a small bandwidth responds slow but results in more precise tracking.

This paper applies adaptive loop techniques commonly deployed in adaptive scalar tracking loops (ASTLs) to alter the loop-bandwidth of the FLL. As a result, the adaptive FLL-ANF (AFLL-ANF) responds much better against jump discontinuities by temporarily increasing the loop-bandwidth before settling back to a smaller loop-bandwidth once it is on the chirp signal. In recent publications, the loop-bandwidth control algorithm (LBCA) has shown promising results for adapting tracking global navigation satellite system (GNSS) receiver tracking loops, and in this paper, it is applied to a new application for FLL-based notch filters. Initial results indicate improved tracking errors compared to fixed-tuned FLL-ANFs and superior alpha-mean values.

Resilient Interference Mitigation with Adaptive FLL-based Adaptive Notch Filtering

what3words: a simpler way to talk about location

Session 1.4.

Maritime incidents rates, the relative likelihood that a vessel has an accident per unit, are a useful metric for navigation authorities in understanding under which conditions and which areas vessels are more at risk of an accident. Understanding where and why accident rates vary supports targeted and cost-effective application of risk controls.

Vessel traffic data from the Automatic Identification System (AIS), principally developed for collision avoidance, has increased in availability and provides significant wider opportunities for navigation safety applications. Unfortunately, calculating spatial accident rates are subject to key methodological challenges associated with the Modifiable Areal Unit Problem that can influence the statistical validity of derived results. This phenomenon that has not been well explored in the maritime domain and requires further investigation.

This paper compares and contrasts accident rates across the United States calculated using 2.5 billion ship positions from AIS for 2018 and 130,000 accidents from the US Coastguard. Given the size and scale of the analysis, a workflow utilising big data processing technologies is developed for national risk mapping. The impacts on accident rates are evaluated of utilising three spatial data structures at different resolutions: namely administrative regions, cartesian regular grids and the Discrete Global Grid System (DGGS).

The results show significant variation in results can be achieved, exhibiting many of the hallmarks of the Modifiable Areal Unit Problem. In particular, such a method has limited utility at performing high resolution analysis, due to the sparsity of accident data, and therefore alternative methods are proposed. Of the three structures investigated, the DGGS exhibits some advantageous properties for regional scale analysis and is recommended for future navigation safety studies. This paper provides greater awareness of issues of spatial modelling for maritime risk analysis and highlight several actions which can be taken by researchers to mitigate them.

Geospatial Mining of Massive AIS Data for Strategic Management of Maritime Navigation Safety: Methodological and Policy Considerations

Session 1.5.

The paper presents a new positioning method based on a Generalised Spatial Correlation of GNSS signals for vehicles moving on geo-referenced tracks. Such location approach allows to detect the closest position ranges to predetermined locations by predicting the phase of satellites’ signals at and in proximity to the referenced locations, by testing the match between the predicted signals and those received by the non standard GNSS receiver.

The gain in sensitivity obtained by cumulating the multi-satellite spatial correlation, associated with the knowledge of the track path, makes it possible to reinforce the reliability of the detection of passage at the referenced spots (concept of virtual balise) and to improve the accuracy of dating and position, reducing the protection radius associated with the single instant of passage of the mobile compared to classical RAIM like monitoring methods.

In addition to the SNR gain brought by cumulating satellite intercorrelation functions, the method of spatial correlation also makes it possible to benefit from a better robustness with respect to specular multipaths. In presence of multipaths delayed with respect to the direct signal, and although the time correlation function is distorted and not symmetrical, the position of the maximum correlation remains unchanged.

The Generalized Spatial Correlation can be used in static and dynamic applications for estimating in real time the "best" position likelihood, based on the sole estimation of the correlation maximum according to 3D space. It is more robust than a classical PVT estimation, based on individual time based correlation using dedicated discriminators sensitive to the distortion of the correlation function.

The duration of exposure of the function being limited to the duration of passage of the mobile near the virtual balise, the risks of non-integrity of the GNSS signal due to local environment are also reduced.

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On the Positioning Performance of VDES R-Mode

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