Autonomuous transportation systems require navigation performance with a high level of integrity. As Global Navigation Satellite System (GNSS) real-time kinematic (RTK) solutions are needed to ensure lane level accuracy of the whole system, these solutions should be trustworthy, which is often not the case in urban environments. Thus, the prediction of integrity for specific routes or trajectories is of interest. The carrier-to-noise density ratio (C/N0) reported by the GNSS receiver offers important insights into the signal quality, the carrier phase availability and subsequently the RTK solution integrity. The ultimate goal of this research is to investigate the predictability of the GNSS signal strength. Using a ray-tracing algorithm together with known satellite positions and 3D building models, not only the satellite visibility but also the GNSS signal propagation conditions at waypoints along an intended route are computed. Including antenna gain, free-space propagation as well as reflection and diffraction at surfaces and vegetation, the predicted C/N0 is compared to that recorded by an Septentrio Altus receiver during an experiment in an urban environment in Hannover. Although the actual gain pattern of the receiving antenna was unknown, good agreements were found with small offsets between measured and predicted C/N0.

For safety critical applications like autonomous driving, high trust in the reported navigation solution is mandatory. This trust can be expressed by the navigation performance parameters, especially integrity. Multipath errors are the most challenging error source in GNSS since only partial correction is possible. In order to ensure high integrity of GNSS-based urban navigation, signal propagation mechanisms and the potential error sources induced by the complex measurement environment should be sufficiently understood. In this contribution, we report on recent progress on this topic in our group. We conducted various experiments in urban areas and investigated the behavior and magnitude of GNSS signal propagation errors. To this end, ray tracing algorithms combined with 3D city models are implemented to identify propagation obstructions and quantity propagation errors. A Fresnel zone-based criterion is exploited to determine the occurrence and magnitude of diffraction. GNSS Feature Maps are proposed to visualize the analyses and to predict situations with potential loss of integrity. To measure the integrity of urban navigation, we developed alternative set-based approaches in addition to the classical stochastic approach. Based on interval mathematics and geometrical constraints, they are sufficient to bound remaining systematic uncertainty and feasible for integrity applications.

Network RTK technique provides the most precise absolute solution among any other navigation methods. So, it plays an important role in the increasing world of autonomy. In addition, integrity monitoring is of great importance in autonomous positioning. In this contribution, the performances of different commercial RTK systems are investigated to evaluate the integrity of the N-RTK solution. We conducted a static experiment in a very good sky visibility condition and kinematic experiments in the urban environments of Hannover. Four commercial RTK receivers including a Leica GS18 T, a Trimble R12i, a u-blox ZED-F9P and a Septentrio Altus NR3 were used. For the static part, these receivers were mounted on stationary pillars with very good satellite visibility and gathered N-RTK solution as well as raw observations for half an hour in 10 Hz. These results serve as a reference for more challenging environments in kinematic part. In the next step, the receivers were mounted on the roof top of a van. The van drove, repeating 1 km loop twelve times. In order to understand the positional variations of the N-RTK solutions, some parameters which show the quality of the raw data e.g., number of visible satellites, signal strength, signal continuity and also multipath and Melbourne-Wübbena linear combinations are investigated showing the challenging in urban areas. Also, the highly variable quality of the receiver-internally logged N-RTK solution was assessed using solution type (code, float, fixed), CQ (Coordinate Quality) of the solution calculated by the receiver, horizontal and vertical deviations of the RTK from the reference trajectory obtained from GNSS-IMU highlighting the impact of the variable satellite. The reliability analysis in form of Stanford diagram shows at best around 14% of nominal operation.

High accuracy positioning is an important part in the future applications of the Intelligent Transportation Systems (ITS) such as autonomous driving in urban environments. Global Navigation Satellite System (GNSS) exploiting differential techniques from reference stations namely Real Time Kinematic (RTK), is capable to provide the most precise and accurate absolute solution for a navigation system. Network RTK uses several reference stations to produce corrections which provide the availability of the service in a wider area. Integrity measures such as Protection Level (PL) and Position Error (PE) are parameters that can give an indicator about the quality of the positioning. In urban environments where the surrounding buildings obscure the signals coming from the satellites, the signal coming to the receiver may fall into four different situations: line-of-sight (LOS), non-line-of-sight (NLOS), multipath and blocked. In these areas the number of available signals for positioning decreases and also some of the available signals reach the receiver in multipath or NLOS conditions, which degrade the signal strength as well as inducing respective errors in code and phase observations. For this contribution a kinematic test was performed in urban environments of city Hannover, mounting RTK receiver on top of a van driving 1 km loop for twelve times. The reference trajectory is calculated by tightly coupling the GNSS data with a high grade IMU data. The GPS/GLONASS RTK corrections are provided by the local service provider (SAPOS). Having a level 2 of details (LoD2) 3D city model, it is possible to use the known ephemerides of the satellites to predict the signal availability for a specific receiver position considering NLOS and multipath situations. This prediction of the satellite visibility, is then used in an Extended Kalman Filter (EKF) to solve the positioning problem. As this solution is based on the predicted visible satellites, it works as a prediction of the positioning. Based on this solution, the Protection Levels (PL) are calculated. The Ray Tracing algorithm also provides us with the code and phase observation errors caused by NLOS and multipath cases. These errors (assuming that they are the main driving errors for deviation in the coordinates domain) are then feed to our positioning algorithm as the observation vector to have an estimate of the position error (PE). On the other hand, the receiver itself provides an estimate of the PL. We calculate the PE by comparing the RTK solution of the receiver and the reference trajectory. Finally, we compare the predicted PL and PE with the real observed PL and PE, considering a horizontal alert limit (HAL) of 10 cm. The results so far, show a partial agreement between the PLs of the predicted and the real data, but there is more space for improvement by considering the C/N0 degradation of the signals and large multipath or NLOS signals. The route will be selected based on reliable solutions which are evaluated by the percentage of the nominal operation in each round.