Initial test of the proposed medium frequency R-Mode navigation message in the Baltic
Bibliographic record
Abstract
R-Mode is a promising technology to support safe navigation at sea. It provides complementary navigation signals to Global Navigation Satellite Systems (GNSS) in the medium frequency (MF) and/or very high frequency (VHF) band with a maritime terrestrial system. Due to the significantly lower transmission frequency, the R-Mode signals are not affected by the same threats and natural error influences as GNSS. R-Mode is therefore an ideal data source for the multi-system shipborne radionavigation receiver specified by the International Maritime Organization (IMO) to improve reliability and availability of position, velocity and timing (PVT) information and to support navigation and shipboard functions. R-Mode Baltic is a testbed in the Baltic Sea region which provides MF R-Mode signals of up to eight transmitting sites distributed across Germany, Sweden, Denmark and Poland. Furthermore, several temporary VHF R-Mode transmitter installations exist in an extended region in Poland, Norway and Germany. These installations were used to design the R-Mode signals, to learn how to implement R-Mode into existing maritime radio infrastructure as well as to test and validate the developed equipment. The knowledge gathered through these activities was used to support the R-Mode standardization at the International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA). Moreover, further R-Mode research and development activities are ongoing in South Korea, US, UK, Canada and Romania. In 2023 the MF R-Mode transmitting sites of the R-Mode Baltic testbed broadcasted the R-Mode signals by combining the 100 bits/s MSK modulated data stream of the maritime radiobeacons and two additional carriers which carry the R-Mode timing information. The additional information about timing errors of the transmitted signals and other static and dynamic data corrections of the transmitting site were not broadcasted. These data, which are fundamental to obtain receiver performance improvement, are usually provided as navigation data by the system service provider. Inspired by the Galileo standard for navigation data and by adapting it to the needs of the MF R-Mode system, we proposed an R-Mode navigation message which can be broadcasted together with the station legacy service, aimed at the provision of code differential corrections for GNSS (DGNSS). Like DGNSS the R-Mode navigation message will follow the RTCM 2 standard of the message design. We introduced a new message with ID 55. The information about the R-Mode transmitting station like identification and status will be sent most frequently in the header of message 55. Four submessages were defined for the static (e.g. coordinates) and dynamic (e.g. clock error and health status) transmitter information. Additionally, two submessages were created during the work at IALA on the R-Mode standard to cover supplementary information from a differential R-Mode service, which were first tested in South Korea. This work is an essential basis for a guideline on Medium Frequency signal structure and navigation message, which is currently being developed at IALA and which is planned to be finalized in 2024. In preparation of the work for the project ORMOBASS, which aims to setup first core operational R-Mode functionalities in the Baltic Sea region, we wanted to prepare the German MF R-Mode sites and make a first test of the navigation information that we plan to broadcast within the upcoming three years. For this purpose, the transmitting sites in Germany were modified to reduce sudden jumps in the phase of the broadcasted R-Mode signal. Furthermore, we established for some days an MF R-Mode reference station at the island Fehmarn which is few tens of km away from the center between the three German MF R-Mode transmitting sites in Groß Mohrdorf, Zeven and on Helgoland. In addition, the Danish R-Mode transmitter on Bornholm could be received. Considering that we were not able to generate and broadcast the R-Mode navigation message directly from the transmitting sites we followed the approach to use the measurements of the reference station to derive all the necessary information and generate the navigation information that was distributed over the internet. At the same time a vessel of the DLR was equipped with an MF R-Mode receiver which was developed over recent years by DLR. The receiver was able to retrieve the navigation information by exploiting standard communication network and process this information to provide a positioning solution to the vessel. Moreover, for the first time we were able to perform positioning without using a GNSS-stabilized rubidium clock. By using predicted Atmospheric and Ground Delay Factor (AGDF) correction maps and an azimuth dependent correction function, we achieved a 95% positioning accuracy of 37 m at daytime and 86 m at nighttime when the vessel was sailing up to 9 km away from the reference station. Despite some technical problems which reduced the expected positioning performance, the receiver advancement in the processing of MF R-Mode signals remains remarkable and the achieved performance is suitable to support coastal navigation with R-Mode as backup system for GNSS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".