Currently Global Navigation Satellite Systems (GNSSs) are the primary source for the determination of absolute position, navigation, and time (PNT) for merchant vessel navigation. Nevertheless, the performance of GNSSs can strongly degrade due to space weather events, jamming, and spoofing. Especially the increasing availability and adoption of low cost jammers lead to the question of how a continuous provision of PNT data can be realized in the vicinity of these devices. In general, three possible solutions for that challenge can be seen: (i) a jamming-resistant GNSS receiver; (ii) the usage of a terrestrial backup system; or (iii) the integration of GNSS with other onboard navigation sensors such as a speed log, a gyrocompass, and inertial sensors (inertial measurement unit—IMU). The present paper focuses on the third option by augmenting a classical IMU/GNSS sensor fusion scheme with a Doppler velocity log. Although the benefits of integrated IMU/GNSS navigation system have been already demonstrated for marine applications, a performance evaluation of such a multi-sensor system under real jamming conditions on a vessel seems to be still missing. The paper evaluates both loosely and tightly coupled fusion strategies implemented using an unscented Kalman filter (UKF). The performance of the proposed scheme is evaluated using the civilian maritime jamming testbed in the Baltic Sea.

R-Mode is a terrestrial navigation system under development for the maritime domain that provides backup in case of a GNSS outage. This paper describes the first test results for real-time positioning on board a ship using medium frequency R-Mode signals. The estimation and positioning algorithms used are described in detail and it is shown how they are integrated into the R-Mode receiver developed by the German Aerospace Center. Moreover, during two daytime experiments with lower and higher dynamic movements of a ship in the Baltic Sea, we were able to achieve a 95% horizontal positioning accuracy of better then 12 m in the center of three R-Mode transmitters. This demonstrates the first time that the medium frequency R-Mode has provided positioning at sea.

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.

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.

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.

Position, navigation, and timing information are critical to today’s infrastructures; as a result, the possibility of estimating ranges is being explored in more and more radio systems. One way to achieve this is to extend the modulation with time-synchronised aiding carriers and to estimate their phase at the receiver side. In this paper, we present two ways to minimise the negative influence of the modulation on the phase estimation. We show that the classical maximum likelihood estimator is still an efficient estimator for our problem, using a medium-frequency R-Mode signal as an example, and is therefore used in receiver designs. We then describe two possible ways to precondition the signal to increase the accuracy for short observations. As a first approach, we describe how window functions can positively change the signal-to-noise ratio for our estimation. As a second approach, we show the use of a narrowband bandpass filter. Finally, we show that these approaches, applied to real measurements, improve the variance of the estimate by up to two orders of magnitude.