Search Results (7)

This paper investigates the impact of atmospheric conditions on distance determination accuracy in the VDES R-Mode system, based on system development and long-term analytical work conducted within the ORMOBASS project. A dedicated VDES R-Mode transmitter and monitoring station were developed and deployed in Poland, in the Port of Gdynia and at the boatswain’s office in the port of Jastarnia, respectively. Both stations were synchronized in time and frequency using a fiber-optic link and White Rabbit technology, ensuring high-precision and stable operation during long-term measurements. Based on a one-year stationary measurement campaign, a comprehensive dataset combining ranging results and meteorological observations was collected and analyzed. Statistical evaluation demonstrated that atmospheric conditions—particularly rainfall intensity and water vapor density—have a measurable impact on ranging accuracy. These findings motivated the development of a mathematical model describing the relationship between atmospheric conditions and distance measurement errors. The proposed logarithmic regression-based approach was validated using real measurement data; the authors also demonstrated its ability to reduce error variability during changing weather conditions, indicating its potential for future implementation in VDES R-Mode receivers. Full article

Accurate prediction of shipping freight indices, represented by the Baltic Dry Index (BDI), is crucial for operational decision-making and risk management in the shipping industry. Existing models mainly rely on historical time-series data and often overlook the influence of unstructured information such as market sentiment. To address this limitation, this study proposes a dynamic freight rate prediction framework integrating a shipping text sentiment index. First, a shipping news sentiment index is constructed using a RoBERTa-based pre-trained model to quantify the impact of market sentiment on freight rate fluctuations. Second, the BDI series is decomposed and reconstructed through Variational Mode Decomposition (VMD) and Fuzzy C-Means (FCM) clustering to extract multiscale features. Finally, a deep learning based multi-step prediction model is developed by incorporating the sentiment index into the forecasting process. Empirical results show that the proposed model significantly outperforms benchmark models without sentiment information in terms of MAE, RMSE, and R², and demonstrates greater robustness under extreme market conditions. These findings provide a novel methodological framework for improving freight rate forecasting accuracy and offer practical decision support for shipping enterprises. Full article

A method for reconstructing weekly Baltic gridded sea levels was developed and tested. This method uses input data from tide gauge and altimetry observations. The reconstruction is based on sea level empirical orthogonal function (EOF) modes, calculated as spatiotemporal statistics from daily model reanalysis results available from the Copernicus Marine Service for the 1993–2021 period. In the semi-enclosed, tideless Baltic Sea, the four leading EOF modes cover 99% of the sea level variance. Several experiments with different combinations of input data were carried out. This method was validated against coastal tide gauges and altimetry data. The best reconstruction was obtained when both the tide gauges and altimetry data were used as inputs. An assessment of the centered root-mean-square difference (cRMSD) of the reconstruction versus the tide gauges revealed a value of 0.05 m, and a result of 0.10 m was revealed versus altimetry. The average coefficient of determination (R²) was determined to be 0.93 for the tide gauges and 0.82 for the altimetry data. In the cases where only one type of input data was used, the reconstruction worsened with respect to other data sources. The reconstruction method demonstrated its usefulness for the reconstruction of coastal sea levels in unsampled locations and the calculation of changes in sea volume. Full article

Time delays caused by ground wave propagation are the primary source of systematic error limiting the performance of the medium-frequency R-Mode radionavigation system. To achieve the desired ranging accuracy and compensate these delays, we have conceived a comprehensive correction scheme based on the prediction and application of the Atmospheric and Ground wave Delay Factor (AGDF). The AGDF was computed and mapped in 2D for a number of MF R-Mode transmitters in the Baltic Sea that were embedded into the receiver and evaluated during a large-scale measurement campaign. Our results show that the proposed AGDF approach is valid for the MF R-Mode system and provides accurate corrections of ground wave propagation delays within the performance requirements. Full article

Terrestrial radio navigation systems are an important data source for increasing the integrity of position, navigation, and timing information and for strengthening the immunity to the spoofing and jamming of satellite-based systems. A possible solution for maritime use is the medium frequency R-Mode. Here, the first real results were presented in the Baltic Sea within the R-Mode Baltic project. For the development of receivers and future signal evolution of R-Mode, there is a great need to provide simulated signals to the receiver hardware. For our laboratory work, we developed different hardware in the loop test systems which enable the simulation of each of the three components and the entire medium frequency R-Mode signal. With this setup, we are able to conduct reproducible tests of the R-Mode receiver’s ranging and positioning performance without the necessity of field tests. Furthermore, the impact of R-Mode signal modifications can be initially analyzed without the need of an implementation in the real-world test bed. Firstly, we describe the usage of arbitrary wave generators that can be used to replay received or simulated signals. Due to their wide distribution in electronic laboratories, there are cost-efficient ways to build up test capabilities. For this work, we tested the Tektronix AFG 3022 and the Rigol DG1032. For further tests, we utilize software-defined radios that are capable of streaming continuous signals. We utilize the ETTUS N210 to directly output the simulated signals. Additionally, we test the LimeSDR with an external down-converter. To generate these signals, we utilize software packages that were created to support the development of the digital signal processing. This approach allows us to test our receiver with a continuous integration from pure software to hardware in the loop test. A comprehensive summary gives an overview of the pros and cons for the different suggested systems. Full article

Global Navigation Satellite Systems (GNSS) are the primary source of position, navigation and timing (PNT) information in the maritime domain. Nevertheless, there is a pressing need for alternative absolute position information to serve as a backup when GNSS is not trustworthy or usable. One possible alternative navigation system is the terrestrial Ranging Mode, also known as the R-Mode. It reuses medium frequency (MF) radio beacons and base stations of the very high frequency data exchange system (VDES) for the transmission of synchronised signals in the service areas of those stations. A large-scale R-Mode testbed is available in the southern Baltic Sea with eight MF radio beacons transmitting R-Mode signals. These signals suffer the self-interference generated by the reflection of the radio wave from the ionosphere at night. The reflected signal, known as the sky wave in the literature, is a form of multipath, which decreases the accuracy of the system. In our work, we present the analysis of measurements obtained with the research vessel Deneb. The horizontal accuracy achieved in the optimal condition was 15.1 m (95%), whereas under the sky wave, the accuracy decreased to 55.3 m. The results are a starting point for the further development of the MF R-Mode system. Full article

The Ranging Mode (R-Mode), a maritime terrestrial navigation system under development, is a promising approach to increase the resilient provision of position, navigation and timing (PNT) information for bridge instruments, which rely on Global Navigation Satellite Systems (GNSS). The R-Mode utilizes existing maritime radio infrastructure such as marine radio beacons, which support maritime traffic with more reliable and accurate PNT data in areas with challenging conditions. This paper analyzes the potential service, which the R-Mode could provide to the mariner if worldwide radio beacons were upgraded to broadcast R-Mode signals. The authors assumed for this study that the R-Mode is available in the service area of the 357 operational radio beacons. The comparison with the maritime traffic, which was generated from a one-day worldwide Automatic Identification System (AIS) Class A dataset, showed that on average, 67% of ships would operate in a global R-Mode service area, 40% of ships would see at least three and 25% of ships would see at least four radio beacons at a time. This means that R-Mode would support 25% to 40% of all ships with position and 67% of all ships with PNT integrity information. The relatively high number of supported ships compared to the total radio beacon coverage of about 9% of the earth’s surface is caused by the good coverage of busy ports and areas such as the coast of China, North Sea and Baltic Sea. These numbers emphasize the importance of marine radio beacons for the R-Mode system. Full article