“…Previous studies have demonstrated that the local geometry of satellites significantly influences the performance of GNSS positioning (refer to [5] and [18], and the citations therein). The geometry is dependent on the receiver's geographical location, as well as line-of-sight (LOS) in the local environment and the placement of the receiver [19], [20]. For instance, in urban canyons, which are common in city areas, tall buildings may obstruct GNSS signals, resulting in a limited LOS (see Figure 2).…”
Section: B Satellite Geometry and Line-of-sightmentioning
Cooperative, connected, and automated mobility (CCAM) can lead to a significantly improved transport system by increasing safety and efficiency, and reducing emissions. To achieve the goal of fully automated mobility and self-driving vehicles, accurate and reliable positioning is essential. Positioning methods in CCAM often use sensor fusion combining data from multiple sensors with Global navigation satellite system (GNSS) positioning data. In this paper, we focus on the status of GNSS technology by investigating position accuracies and integrities of different state-of-the-art GNSS technologies. We conduct field tests using a self-driving vehicle in Drammen, Norway. Three different types of GNSS positioning services are explored, and a reference trajectory delivered by the vehicle's navigation system is used to determine the performance of each service. We show that the performance of the GNSS methods alone does not fulfill the requirements needed to obtain fully automated mobility. Moreover, we observe a general decreasing trend in GNSS accuracy for more challenging surroundings.
“…Previous studies have demonstrated that the local geometry of satellites significantly influences the performance of GNSS positioning (refer to [5] and [18], and the citations therein). The geometry is dependent on the receiver's geographical location, as well as line-of-sight (LOS) in the local environment and the placement of the receiver [19], [20]. For instance, in urban canyons, which are common in city areas, tall buildings may obstruct GNSS signals, resulting in a limited LOS (see Figure 2).…”
Section: B Satellite Geometry and Line-of-sightmentioning
Cooperative, connected, and automated mobility (CCAM) can lead to a significantly improved transport system by increasing safety and efficiency, and reducing emissions. To achieve the goal of fully automated mobility and self-driving vehicles, accurate and reliable positioning is essential. Positioning methods in CCAM often use sensor fusion combining data from multiple sensors with Global navigation satellite system (GNSS) positioning data. In this paper, we focus on the status of GNSS technology by investigating position accuracies and integrities of different state-of-the-art GNSS technologies. We conduct field tests using a self-driving vehicle in Drammen, Norway. Three different types of GNSS positioning services are explored, and a reference trajectory delivered by the vehicle's navigation system is used to determine the performance of each service. We show that the performance of the GNSS methods alone does not fulfill the requirements needed to obtain fully automated mobility. Moreover, we observe a general decreasing trend in GNSS accuracy for more challenging surroundings.
“…Papers analysing the results of NRTK measurements referenced to at least two different networks and carried out under a single test procedure (Edwards et al, 2010;Garrido et al, 2012;Uznański, 2017;Specht et al, 2017;Koivula et al, 2018;Gillins et al, 2019;Prochniewicz et al, 2020) are few in number compared to papers presenting the results of measurements referenced to a single network. The authors used a variety of test procedures, the primary purpose of which was to determine the accuracy and precision of NRTK measurement results or individual reference data streams, although other aspects were also tested, such as the importance of positioning support with GLONASS (Martin and McGovern, 2012;Bae et al, 2015;Öğütcü and Kalayci, 2016) system satellites.…”
Section: Introductionmentioning
confidence: 99%
“…In this case, only one receiver can be centrally positioned. In Öğütcü and Kalayci (2016), no receiver was centrally positioned. The two main drawbacks in such a case are the proximity of the receivers, which does not occur outside the test measurements, and the need to determine the orientation of a survey apparatus.…”
Network Real Time Kinematic (NRTK) measurements are currently the most popular surveying method in geodesy. In most countries, there are networks of Continuously Operating Reference Stations (CORS), which form the core of the terrestrial infrastructure that allows for NRTK measurements. In many countries, including Poland, several CORS networks operate in parallel and independently. The paper presents the characteristics of the CORS network in Poland. The results of several day NRTK and Real Time Kinematic (RTK) test measurements performed tied to five CORS networks operating in Poland: ASG-EUPOS, NadowskiNET, SmartNet, TPINETpro, VRSNet.pl, were subjected to a comparative analysis. VRS, FKP, MAC and POJ streams were used in the test measurements. The research mainly concerned the possibility of the occurrence of systematic errors when NRTK and RTK measurements were tied to different CORS networks for the survey of the same points. Conclusions from the comparative analysis of the accuracy and precision of the NRTK and RTK measurement results for each coordinate were also included.
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