An analysis of observations from China's first medium earth orbit satellite Compass M-1 is presented, with main focus on the first orbit and clock solution for this satellite. The orbit is computed from laser ranging measurements. Based on this orbit solution, the apparent clock offset is estimated using measurements from two GNSS receivers, which allow Compass tracking. The analysis of the clock solutions reveals unexpectedly high dynamics in the pseudorange and carrier-phase observations. Furthermore, carrier-to-noise density ratio, pseudorange noise, and multipath are analyzed and compared to GPS and GIOVE. The results of the clock analysis motivate further research on the signals of the geostationary satellites of the Compass constellation.
The EUREF Permanent Network Densification is a collaborative effort of 26 European GNSS analysis centers providing series of daily or weekly station position estimates of dense national and regional GNSS networks, in order to combine them into one homogenized set of station positions and velocities. During the combination, the station meta-data, including station names, DOMES numbers, and position offset definitions were carefully homogenized, position outliers were efficiently eliminated, and the results were cross-checked for any remaining inconsistencies. The results cover the period from March 1999 to January 2017 (GPS week 1000-1933) and include 31 networks with positions and velocities for 3192 stations, well covering Europe. The positions and velocities are expressed in ITRF2014 and ETRF2014 reference frames based on the Minimum Constraint approach using a selected set of ITRF2014 reference stations. The position alignment with the ITRF2014 is at the level of 1.5, 1.2, and 3.2 mm RMS for the East, North, Up components, respectively, while the velocity RMS values are 0.17, 0.14, and 0.38 mm/year for the East, North, and Up components, respectively. The high quality of the combined solution is also reflected by the 1.1, 1.1, and 3.5 mm weighted RMS values for the East, North, and Up components, respectively.
First results are presented for precise (mm/cm-level) short-baseline RTK positioning based on single-frequency GPS data combined with data of GIOVE-A/B, the two experimental Galileo satellites, collected in Australia. The paper first focuses on the model of GPSþGalileo observation equations and addresses the issues that arise when combining data of both systems, in particular the inter-system biases (ISBs). Our results indicate that the differential ISBs are quite stable in time, potentially enabling calibration and a priori correction of the Galileo phase and code observations. Based on ISB-corrected data, the reliability of single-frequency GPSþGIOVE ambiguity resolution is significantly improved, when compared to GPS only.
In the next five to ten years, the evolution of Global Navigation Satellite Systems (GNSSs) will have a revolutionary impact on the positioning performance. More GNSSs will become available with improved signal characteristics. At the same time, enhancement of receiver technology and algorithms is ongoing. In light of these developments, it is investigated whether highprecision relative positioning with single-frequency receivers will become feasible, and, if so, under which circumstances. We submit that this would open the door to a wide range of applications for instance in the field of mobile Location Based Services for which users do not have professional receivers at their disposal. The closed form expression of the single-frequency Ambiguity Dilution of Precision (ADOP) gives a clear insight into how and to what extent the various factors of the underlying singlefrequency model contribute to the overall ambiguity resolution performance. Furthermore, numerical studies indicate that for benign dynamics single-frequency RTK becomes feasible for baselines up to about 10-15 km if GPS+Galileo is used. In this contribution we will present analytical and numerical results. Ambiguity resolution performance as function of number of epochs, receiver noise and baseline length will be analyzed, and compared for ideal circumstances as well as for situations with bad satellite visibility and/or multipath. Furthermore, different next generation GNSS configurations will be considered. Based on the results, it is predicted that for rapid, short baseline cm-level positioning, low-cost single-frequency receivers will become very competitive in comparison to their more expensive dual-frequency cousins.
We present a local quasi‐geoid (QG) model which combines a satellite‐only global gravity model with local data sets using weighted least squares. The QG is computed for an area comprising the Netherlands, Belgium, and the southern North Sea. It uses a two‐scale spherical radial basis function model complemented by bias parameters to account for systematic errors in the local gravity data sets. Variance factors are estimated for the noise covariance matrices of all involved data sets using variance component estimation. The standard deviation (SD) of the differences between the computed QG and GPS/leveling data is 0.95 and 1.52 cm for the Netherlands and Belgium, respectively. The fact that the SD of the control data is about 0.60 and 1.20 cm for the Netherlands and Belgium, respectively, points to a lower mean SD of the computed QG model of about 0.7 cm for the Netherlands and 1.0 cm for Belgium. The differences to a QG model computed with the remove‐compute‐restore technique range from −5.2 to 2.6 cm over the whole model domain and from −1.5 to 1.5 cm over the Netherlands and Belgium. A variogram analysis of the differences with respect to GPS/leveling data reveals a better performance of the computed QG model compared to a remove‐compute‐restore‐based QG model for wavelengths >100 km for Belgium but not for the Netherlands. The latter is due to the fact that at the spatial scales resolved by the global gravity model, variance component estimation assigns significantly lower weights to the local data set in favor of the global gravity model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.