Research on GNSS and RTK Performance for V2X Application Scenarios

Though unmanned aircraft systems (UAS) are widely used in agriculture, their current positioning accuracy in a radius of 0.5 to 2 meters is still too low to pinpoint a crop row or to precisely overlay temporal multi-source field maps together without a valid geometric calibration. The positioning accuracy of UAS deployed with real time kinematic (RTK) global navigation satellite system (GNSS) can be largely increased to a centimeter level, which was claimed from the manufacturers. This paper includes the preliminary test results of positioning accuracy of a commercial RTK UAS over a set of fixed position panels in our customized scenarios. Images were collected in three GNSS modes (regular GNSS without RTK, RTK mode 1 - not corrected by the positioning error of the base station, and RTK mode 2 - corrected by the positioning error of the base station) in static and in-flight settings. In the static setting, horizontal accuracies were 2.17 cm for the RTK mode 2, 12.11 cm for the RTK mode 1, and 11.46 cm for the regular GNSS mode. The significant result of horizontal accuracy in the in-flight setting was that RTK mode 2 without GCPs (2.82 cm) showed comparable accuracy with the commonly used regular GNSS mode with GCPs (1.34 cm). The vertical positioning accuracy in the static setting were 6.01 cm for the RTK mode 2, 5.65 cm for the RTK mode 1, and 10.48 cm for the regular GNSS mode. The accuracy of height measurement from digital surface models (DSMs) without and with GCPs in RTK mode 2 were 4.81 cm and 3.72 cm, respectively, which were the best performance among the three modes. In summary, the RTK UAS tested in this study showed great potential in eliminating the requirement of using GCPs and in high-positioning-accuracy application. The next phase is to test the system in field for accurate crop height measurement at different growth stages in agricultural application.

Tropospheric delay is a major error source that affects the performance of the Global Navigation Satellite Systems (GNSS) Real Time Kinematic (RTK) positioning especially for the medium/long-range baseline. Although high precision tropospheric delay can be estimated by GNSS carrier phase measurement, together with position and ambiguity, a relatively long period of convergence time is necessary. In this study, we develop a new GPS/BDS RTK algorithm constrained with a tropospheric delay parameters from Numerical weather prediction (NWP) model for medium/long-range baselines. The accuracy of the tropospheric delays derived from NWP is assessed through comparisons with the results of GAMIT (GNSS at MIT). The positioning performance with standard GPS RTK, standard GPS/BDS RTK, the developed NWP-constrained GPS RTK and NWP-constrained GPS/BDS RTK over medium/long-range baselines are compared in terms of the initialization time and the positioning accuracy. Experiment results show that the mean differences between the NWP and GAMIT zenith tropospheric delay (ZTD) are between −5.50 mm and 5.60 mm, and the RMS values of the NWP ZTD residuals are from 24.02 mm to 32.62 mm. A reduction in the initialization time of over 41% and 58% for medium- and long-range baselines can be achieved with the NWP-constrained RTK (both GPS alone and GPS/BDS RTK solutions) compared to the standard RTK solution, respectively. An improvement of over 30% can be found with the GPS/BDS RTK compared with that of the GPS alone RTK for both standard and the NWP-constrained modes. The positioning precision of NWP-constrained GPS/BDS RTK is better than 3 cm in the horizontal direction and better than 5 cm in the vertical direction, which satisfies the requirement of the precise positioning service.

During the past few decades, the presence of global navigation satellite systems (GNSSs) such as GPS, GLONASS, Beidou and Galileo has facilitated positioning, navigation and timing (PNT) for various outdoor applications. With the rapid increase in the number of orbiting satellites per GNSS, enhancements in the satellite-based augmentation systems (SBASs) such as EGNOS and WAAS, as well as commissioning new GNSS constellations, the PNT capabilities are maximized to reach new frontiers. Additionally, the recent developments in precise point positioning (PPP) and real time kinematic (RTK) algorithms have provided more feasibility to carrier-phase precision positioning solutions up to the third-dimensional localization. With the rapid growth of internet of things (IoT) applications, seamless navigation becomes very crucial for numerous PNT dependent applications especially in sensitive fields such as safety and industrial applications. Throughout the years, GNSSs have maintained sufficiently acceptable performance in PNT, in RTK and PPP applications however GNSS experienced major challenges in some complicated signal environments. In many scenarios, GNSS signal suffers deterioration due to multipath fading and attenuation in densely obscured environments that comprise stout obstructions. Recently, there has been a growing demand e.g. in the autonomous-things domain in adopting reliable systems that accurately estimate position, velocity and time (PVT) observables. Such demand in many applications also facilitates the retrieval of information about the six degrees of freedom (6-DOF - x, y, z, roll, pitch, and heading) movements of the target anchors. Numerous modern applications are regarded as beneficiaries of precise PNT solutions such as the unmanned aerial vehicles (UAV), the automatic guided vehicles (AGV) and the intelligent transportation system (ITS). Hence, multi-sensor fusion technology has become very vital in seamless navigation systems owing to its complementary capabilities to GNSSs. Fusion-based positioning in multi-sensor technology comprises the use of multiple sensors measurements for further refinement in addition to the primary GNSS, which results in high precision and less erroneous localization. Inertial navigation systems (INSs) and their inertial measurement units (IMUs) are the most commonly used technologies for augmenting GNSS in multi-sensor integrated systems. In this article, we survey the most recent literature on multi-sensor GNSS technology for seamless navigation. We provide an overall perspective for the advantages, the challenges and the recent developments of the fusion-based GNSS navigation realm as well as analyze the gap between scientific advances and commercial offerings. INS/GNSS and IMU/GNSS systems have proven to be very reliable in GNSS-denied environments where satellite signal degradation is at its peak, that is why both integrated systems are very abundant in the relevant literature. In addition, the light detection and ranging (LiDAR) systems are widely adopted in the literature for its capability to provide 6-DOF to mobile vehicles and autonomous robots. LiDARs are very accurate systems however they are not suitable for low-cost positioning due to the expensive initial costs. Moreover, several other techniques from the radio frequency (RF) spectrum are utilized as multi-sensor systems such as cellular networks, WiFi, ultra-wideband (UWB) and Bluetooth. The cellular-based systems are very suitable for outdoor navigation applications while WiFi-based, UWB-based and Bluetooth-based systems are efficient in indoor positioning systems (IPS). However, to achieve reliable PVT estimations in multi-sensor GNSS navigation, optimal algorithms should be developed to mitigate the estimation errors resulting from non-line-of-sight (NLOS) GNSS situations. Examples of the most commonly used algorithms for trilateration-based positioning are Kalman filters, weighted least square (WLS), particle filters (PF) and many other hybrid algorithms by mixing one or more algorithms together. In this paper, the reviewed articles under study and comparison are presented by highlighting their motivation, the methodology of implementation, the modelling utilized and the performed experiments. Then they are assessed with respect to the published results focusing on achieved accuracy, robustness and overall implementation cost-benefits as performance metrics. Our summarizing survey assesses the most promising, highly ranked and recent articles that comprise insights into the future of GNSS technology with multi-sensor fusion technique.

In 5G networks information about localization of a user equipment (UE) can be used not only for emergency calls or location-based services, but also for the network optimization applications, e.g., network management or dynamic spectrum access by using Radio Environment Maps (REM). However, some of these applications require much better localization accuracy than currently available in 4G systems. One promising localization method is Global Navigation Satellite System (GNSS)-based Real-Time Kinematics (RTK). While the signal received from satellites is the same as in traditional GNSS, a new reception method utilizing real-time data from a nearby reference station (e.g., 5G base station) results in cm-level positioning accuracy. The aim of this paper is to obtain a model of the RTK localization error for smartphone-grade GNSS antenna under open-sky conditions, that can be used in 5G network simulators. First, a tutorial-style overview of RTK positioning, and satellite orbits prediction is provided. Next, an RTK localization simulator is implemented utilizing GNSS satellites constellations. Results are investigated statistically to provide a simple, yet accurate RTK localization error framework, which is based on two Gauss-Markov process generators parametrized by visible satellites geometry, UE motion, and UE-satellite distance error variance.

For precise positioning in arctic regions with Global Navigation Satellite Systems (GNSS), such as GPS and Glonass, there are a number of issues to be resolved or taken into account. The most important ones are satellite geometry, ionospheric effects and distribution of correction data. Precise Point Positioning (PPP) is currently the standard for precise offshore positioning. PPP requires a sparse global network of GNSS reference stations to estimate precise satellite orbit and clock parameters in real-time. These parameters are transmitted to users, who can compute their position with an accuracy of 0.1 m using code and carrier observations. The main disadvantage of PPP is that in general it takes a long time to converge to this accuracy, about 30–45 minutes. GNSS carrier observations are similar to pseudo ranges, but have an additional bias which needs to be estimated. Under certain conditions, these biases are integer. This property is used in what is generally referred to as Real-Time Kinematic (RTK) positioning, a technique which uses corrections generated at reference stations to make sure these ambiguities are integer. Integer Ambiguity Resolution (IAR) results in RTK accuracies of 0.01–0.03 m or better and short convergence times, ranging from instantaneous to several minutes for long inter-station distances. The disadvantage is the limited area of applicability, because RTK in general does not use precise orbits and clocks. Current research focuses on the combination of PPP and RTK techniques. The main goal is to achieve cm accuracy with a sparse network of reference stations. Another goal is to reduce convergence time. Applications are in the field of precise real-time offshore positioning in general, and subsidence monitoring and tidal estimation in particular. Results will be presented from standard PPP and PPP combined with IAR for arctic regions and from a test bed in the Gulf of Mexico. These results, although preliminary, indicate centimeter level accuracy is indeed possible, also in the arctic. We will also look at further improvements, mainly in convergence time, using all operational satellites and signals from current and future navigation systems.

Interplanetary coronal mass ejections (ICMEs) and the driven geomagnetic storms have a profound influence on the ionosphere, potentially leading to a degradation in positioning performance. In this study, we made a comprehensive analysis of the entire process of the impact of a typical ICME and its driven geomagnetic storm on the low-latitude ionosphere during March 13–14, 2022 (π-day storm) and the positioning performance of Global Navigation Satellite System (GNSS). During the passage of the ICME event, significant ionospheric scintillation, and TEC (total electron content) disturbances were observed in the low-latitude Hong Kong region. The ICME sheath region intensively compressed the magnetosphere via solar wind dynamic pressure enhancement and subsequently drove the storm main phase. It is found that both the magnetospheric compression that formed the storm initial phase and the storm main phase caused ionospheric scintillation. In comparison, the intensity of the ionospheric scintillation caused by the intense magnetospheric compression just before the storm main phase is even more pronounced. We also analyzed the impact of storms on standard point positioning (SPP), precise point positioning (PPP) and real-time kinematic (RTK) techniques. The positioning accuracies of single-frequency SPP and PPP experienced the most severe decline, and there was a noticeable increase in the initialization time for dual-frequency static PPP and RTK during the event. RTK demonstrated a shorter convergence time and higher accuracy during this event, but it was limited to short-baseline RTK (<30 km).

Sistem pelacakan senjata telah menjadi elemen krusial dalam berbagai aplikasi militer dan keamanan, memungkinkan deteksi, pelacakan, dan identifikasi yang akurat terhadap perangkat senjata. Penelitian ini membahas pengembangan dan implementasi sistem pelacakan senjata yang berbasis pada modul Global Navigation Satellite System (GNSS) single band dengan memanfaatkan teknologi Real Time Kinematic (RTK) guna mencapai tingkat presisi dan akurasi yang tinggi dalam pelacakan senjata. Pada tahap awal, penelitian ini menganalisis karakteristik GNSS dan prinsip dasar RTK, serta menjelajahi berbagai pilihan modul GNSS single band yang sesuai untuk aplikasi pelacakan senjata. Selanjutnya, sistem perangkat keras dan perangkat lunak dirancang dan diimplementasikan dengan menggunakan mikrokontroler yang mampu mengakuisisi data GNSS secara real-time dan menghitung posisi senjata dengan tingkat presisi sub-meter.Uji coba lapangan dilakukan untuk mengevaluasi kinerja sistem yang telah dikembangkan dalam berbagai kondisi lingkungan dan situasi penggunaan yang berbeda. Hasil pengujian menunjukkan bahwa sistem pelacakan senjata berbasis modul GNSS single band dengan RTK mampu memberikan tingkat akurasi yang memadai, bahkan dalam lingkungan dengan gangguan sinyal atau pergerakan cepat. Penelitian ini memberikan kontribusi nyata dalam pengembangan teknologi pelacakan senjata dengan mengintegrasikan GNSS single band dan RTK, menghasilkan sistem yang dapat meningkatkan kemampuan operasional dan taktis dalam mendukung keamanan dan pertahanan nasional. Selain itu, temuan dan metodologi dalam penelitian ini dapat diterapkan dalam berbagai aplikasi pelacakan lain di luar domain militer.

Built-up city 'urban canyons' offer an environment which challenges the physical limitations of modem real-time GPS positioning systems and, yet, is perhaps the one environment where the successful application of GPS technology could benefit most users. With a view to the next generation of Real Time Kinematic (RTK) positioning systems, this paper highlights the limitations imposed on current RTK systems operating in the urban canyon using GPS visibility trials conducted in the urban canyon of the Perth Central Business District (CBD). Furthermore, following the recent release of receivers capable of integrating the Global Positioning System (GPS) and the Russian equivalent, the Global Navigation Satellite System (GLONASS), the advantages of integration of both GPS and GLONASS systems are demonstrated using GLONASS visibility simulations at selected points in the Perth CBD.

Bae, T.-S. and Kim, M., 2019. High precision GNSS positioning for the coastal navigation safety of large vessels. In: Lee, J.L.; Yoon, J.-S.; Cho, W.C.; Muin, M., and Lee, J. (eds.), The 3rd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 91, pp. 441-445. Coconut Creek (Florida), ISSN 0749-0208.Over several decades, the Global Navigation Satellite System (GNSS) has been the most important navigation equipment for vessels. Although the C/A code based absolute positioning is sufficient for most cases, a precisely guided coastal navigation is necessary for the entry and the departure of large vessels at a port. More accurate positioning and navigation can be achieved by applying the real-time kinematic (RTK) technique, which uses the carrier phases of the GNSS signals. However, the error is generally proportional to the baseline lengths between the references and the rovers due to the decorrelation of the signals. In this study, the error behavior of a single-baseline RTK (SRTK) was analyzed based on a Continuously Operating Reference Station (CORS) network in Korea. In addition, the network-based RTK (NRTK) correction was used to better estimate the position of large vessels for coastal navigation. Finally, the UP component of the vessel was constrained to the geoid to characterize coastal navigation uniquely.

One of the main methods of the path localization of moving objects is positioning using Global Navigation Satellite Systems (GNSSs) in cooperation with Inertial Navigation Systems (INSs). Its basic task is to provide high availability, in particular in areas with limited access to satellite signals such as forests, tunnels or urban areas. The aim of the article is to carry out the testing and analysis of selected navigation parameters (3D position coordinates (Northing, Easting, and height) and Euler angles (pitch and roll)) of the GNSS/INS system for Unmanned Surface Vehicle (USV) path localization during inland hydrographic surveys. The research used the Ellipse-D GNSS/INS system working in the Real Time Kinematic (RTK) mode in order to determine the position of the "HydroDron" Autonomous Surface Vehicle (ASV). Measurements were conducted on four representative routes with a parallel and spiral arrangement of sounding profiles on Lake Kłodno (Poland). Based on the obtained research results, position accuracy measures of the "HydroDron" USV were determined using the Ellipse-D GNSS/INS system. Additionally, it was determined whether USV path localization using a GNSS/INS system working in the RTK mode meets the positioning requirements for inland hydrographic surveys. Research has shown that the Ellipse-D system operating in the RTK mode can be successfully used to position vessels when carrying out inland hydrographic surveys in all International Hydrographic Organization (IHO) Orders (Exclusive, Special, 1a/1b and 2) even when it does not work 100% correctly, e.g., loss of RTK corrections for an extended period of time. In an area with limited coverage of the mobile network operator (30-40% of the time the receiver operated in the differential mode), the positioning accuracy of the "HydroDron" USV using the Ellipse-D GNSS/INS system working in the RTK mode was from 0.877 m to 0.941 m for the R95(2D) measure, depending on the route travelled. Moreover, research has shown that if the Ellipse-D system performed GNSS/INS measurements using the RTK method, the pitch and roll error values amounted to approx. 0.06°, which is almost identical to that recommended by the device manufacturer. However, when working in the differential mode, the pitch and roll error values increased from 0.06° to just over 0.2°.

Currently Global Navigation Satellite Systems (GNSS) are the primary source for the determination of absolute position, velocity and time (PVT) for merchant vessel navigation. On a ship bridge a number of systems like Electronic Chart and Information Systems (ECDIS), automatic track control systems and the Automatic Identification System (AIS) are relying on that PVT provision. Nevertheless it is well known that GNSS performance can strongly degrade due to space weather events, jamming and spoofing. Especially the availability and usage of low cost jammers, so called personal privacy devices (PPD), lead to the question on how a continuous onboard provision of PVT data can be realized in the presence of such a PPD jammer. Generally three possible solutions for that challenge are contemplated: i) the usage of a terrestrial backup system, ii) a jamming resistant GNSS receiver or iii) the integration of GNSS with other onboard self-contained navigation sensors like, e.g. speed log, gyrocompass and inertial sensors (Inertial Measurement Unit - IMU). The paper will focus on option (iii) and addresses the question whether it is possible to bridge real maritime GNSS Jamming attacks by a Kalman Filter (KF) using GNSS, inertial and Doppler velocity log (DVL). The main challenge for the KF here is, that a free inertial integration needs to be performed after a time period with already degraded GNSS signal reception. As KF are known to be optimum estimators only under the assumption of known statistics of the measurements, the question arises, whether the pseudoranges under the influence of jamming still follow a certain statistics. In order answer this question an additional lab experiment was performed and analyzed. Concretely the sensor fusion was realized by using both loosely and tightly coupled architectures which have been implemented using an Unscented Kalman Filter (UKF). The fusion algorithm is formulated in ECEF coordinate frame with quaternion attitude parameterization, where the heading observability is addressed by fusing the baseline measurements from the GNSS compass. In order to evaluate the performance of the proposed sensor fusion scheme under the influence of a real maritime jamming attack we performed an experiment in our civilian maritime jamming testbed in the Baltic, which has been established together with the German Federal Network Agency approximately 6 nmi north of the peninsula Dars. Here a PPD jammer was mounted on the monkey deck of an anchored vessel. A test vessel was maneuvering around the jammer. As a test vessel the multipurpose research and diving vessel Baltic Diver II (length 29 m, beam 6.7 m and draught 2.8 m) was used, which was equipped with three dual frequency GNSS receivers, a fiber-optic gyroscope IMU and a Doppler velocity log. The obtained results confirm that real maritime jamming attacks using PPD Jammers can be bridged by the proposed tightly coupled GNSS-IMU-DVL integration scheme resulting in horizontal position errors of less than 10m only.

Urban environments present major challenges to the global navigation satellite system (GNSS) positioning to estimate the position of a self-driving vehicle. GNSS signals are often obstructed by buildings and other obstacles, leading to reflected and diffracted signals, which cause major positioning errors and known as line-of-sight (LOS) and non-line-of-sight (NLOS) multipath errors. Particularly, real-time kinematic (RTK)-GNSS, which can estimate the position in the centimeter-level accuracy, cannot estimate the precise position when there exist NLOS multipath errors. If we use NLOS GNSS code and carrier phase multipath measurements into the RTK-GNSS algorithm, carrier phase integer ambiguity cannot be solved, or wrong integer ambiguities are estimated. As a result, integer ambiguity resolved to fix solutions cannot be estimated, or wrong fix solutions which have large position error are estimated. That is a major barrier to using RTK-GNSS in autonomous driving. In this paper, we propose a novel NLOS detection and exclusion technique to enhance existing RTK-GNSS positioning in urban areas using only GNSS measurements alone. The key idea behind the proposed technique is that the NLOS pseudorange error will always be a positive value. NLOS pseudorange is longer than the true range, which is the distance between the GNSS antenna and satellite, due to the time delay caused by reflection and diffraction. The distribution of the NLOS error is not along with a Gaussian distribution. We use this phenomenon to detect the NLOS signals. We propose a technique to detect and eliminate the NLOS multipath using double-differenced pseudorange residuals (DD-PR). In the RTK-GNSS, DD GNSS measurement between the rover and base station is typically used. Here, we compute the DD-PR to detect the NLOS signals. In order to compute the DD-PR, the true position of the vehicle must be determined in advance. To solve this contradiction, we use a particle filter. The particle filter generates the position hypotheses, which is called as “particle”. These particles are used as the position candidate for estimating the DD-PR. When the DD-PR can be calculated at each particle position, we detect the large positive errors in DD-PR as NLOS signals. Then we compute the integer ambiguity of only the LOS DD carrier phase to estimate the precise vehicle position. The flow of the proposed technique is as follows: (1) The hypothetical user positions are created as particles, where the state vectors of these particles are 3D positions, x, y, and z. The initial particles are distributed based on the solution of the normal GNSS point positioning and its variance. (2) In the prediction step of the particle filter, the particle state in the next time step is estimated using the velocity of each particle computed from GNSS Doppler measurements. (3) Next, we compute the DD-PR at each particle location. The receiver clock bias, satellite clock bias, ionosphere error, and troposphere error in GNSS pseudorange are canceled through DD computation. As a result, DD geometrical range between receiver and satellite and DD multipath errors remain in the DD measurement. We compute DD-PR using the particle position. As a result, the only multipath error remains if the particle is close to the true position. NLOS multipath error is always positive value; we generate the subset of the LOS measurement hypothesis at each particle using a simple threshold test. (4) Next, we compute the RTK-GNSS position solution using the generated subset of the LOS measurement hypothesis at each particle location. It is expected that the RTK-GNSS fix solution can be calculated if the particle location is close to the true position because the NLOS signal has been eliminated. By contrast, if the particle is far from true position, the integer ambiguity cannot be solved because of using the incorrect subset of LOS measurements. The likelihood of each particle is computed from a distance between the particle location and the RTK-GNSS fix solution. The particle that is closest to the true position has a higher likelihood than the other particles. The probabilistic weight of each particle is then updated based on its likelihood. (5) Finally, all the particles are resampled based on their new weights. Particles that are sufficiently close to the true position survive this resampling step, and the average position of the remaining particles are employed as the final estimated user position. To confirm the effectiveness of the proposed technique, a kinematic positioning test was performed in Shinjuku, Tokyo, Japan. From the several positioning tests, the proposed technique could dramatically improve the availability and accuracy of RTK-GNSS fix solutions in the dense urban canyon where there exist a lot of NLOS multipath signals.

Uncrewed aircraft systems (UASs) and structure-from-motion/multi-view stereo (SfM/MVS) photogrammetry are efficient methods for mapping terrain at local geographic scales. Traditionally, indirect georeferencing using ground control points (GCPs) is used to georeference the UAS image locations before further processing in SfM software. However, this is a tedious practice and unsuitable for surveying remote or inaccessible areas. Direct georeferencing is a plausible alternative that requires no GCPs. It relies on global navigation satellite system (GNSS) technology to georeference the UAS image locations. This research combined field experiments and simulation to investigate GNSS-based post-processed kinematic (PPK) as a means to eliminate or reduce reliance on GCPs for shoreline mapping and charting. The study also conducted a brief comparison of real-time network (RTN) and precise point positioning (PPP) performances for the same purpose. Ancillary experiments evaluated the effects of PPK base station distance and GNSS sample rate on the accuracy of derived 3D point clouds and digital elevation models (DEMs). Vertical root mean square errors (RMSEz), scaled to the 95% confidence interval using an assumption of normally-distributed errors, were desired to be within 0.5 m to satisfy National Oceanic and Atmospheric Administration (NOAA) requirements for nautical charting. Simulations used a Monte Carlo approach and empirical tests to examine the influence of GNSS performance on the quality of derived 3D point clouds. RTN and PPK results consistently yielded RMSEz values within 10 cm, thus satisfying NOAA requirements for nautical charting. PPP did not meet the accuracy requirements but showed promising results that prompt further investigation. PPK experiments using higher GNSS sample rates did not always provide the best accuracies. GNSS performance and model accuracies were enhanced when using base stations located within 30 km of the survey site. Results without using GCPs observed a direct relationship between point cloud accuracy and GNSS performance, with R2 values reaching up to 0.97.

In sport science, Global Navigation Satellite Systems (GNSS) are frequently applied to capture athletes' position, velocity and acceleration. Application of GNSS includes a large range of different GNSS technologies and methods. To date no study has comprehensively compared the different GNSS methods applied. Therefore, the aim of the current study was to investigate the effect of differential and non-differential solutions, different satellite systems and different GNSS signal frequencies on position accuracy. Twelve alpine ski racers were equipped with high-end GNSS devices while performing runs on a giant slalom course. The skiers' GNSS antenna positions were calculated in three satellite signal obstruction conditions using five different GNSS methods. The GNSS antenna positions were compared to a video-based photogrammetric reference system over one turn and against the most valid GNSS method over the entire run. Furthermore, the time for acquisitioning differential GNSS solutions was assessed for four differential methods. The only GNSS method that consistently yielded sub-decimetre position accuracy in typical alpine skiing conditions was a differential method using American (GPS) and Russian (GLONASS) satellite systems and the satellite signal frequencies L1 and L2. Under conditions of minimal satellite signal obstruction, valid results were also achieved when either the satellite system GLONASS or the frequency L2 was dropped from the best configuration. All other methods failed to fulfill the accuracy requirements needed to detect relevant differences in the kinematics of alpine skiers, even in conditions favorable for GNSS measurements. The methods with good positioning accuracy had also the shortest times to compute differential solutions. This paper highlights the importance to choose appropriate methods to meet the accuracy requirements for sport applications.

Reusable launch vehicles (RLV) in a vertical take-off vertical landing configuration require accurate measurements of the height above the ground during the final descent just before landing. It is proposed to use real-time kinematic positioning (RTK), which is a differential GNSS navigation method requiring a nearby reference GNSS antenna and receiver, to measure the rover's position with centimetre accuracy. The effects of the engine plume, vibration and multipath are challenging when using this carrier-phase based positioning method on an RLV. Especially the residual differential tropospheric error due to the rover and reference GNSS antennas being at different heights, primarily caused by humidity in the air, may hinder the successful fixing of the carrier phase ambiguities. To gain a better understanding of the RTK performance to be expected on a landing RLV, a skydiver experiment was conducted in April 2022. The skydiver was equipped with a rover GNSS receiver and a helmet with a GNSS antenna on top and an independent integrated navigation system serving as reference. The skydiver reached free fall velocities of up to 385 km/h, which is seen representative of the vertical velocity of an RLV. The paper describes the experiment procedure and the results of the experiment.