scholarly journals Improving GNSS PPP Convergence: The Case of Atmospheric-Constrained, Multi-GNSS PPP-AR

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 587 ◽  
Author(s):  
John Aggrey ◽  
Sunil Bisnath
Keyword(s):  
Low Cost ◽  
Research Question ◽  
Convergence Time ◽  
Dual Frequency ◽  
International Gnss Service ◽  
Triple Frequency ◽  
Solution Convergence ◽  
Global Ionospheric Maps ◽  
Future Work

GNSS positioning performance has been shown to improve with the ingestion of data from Global Ionospheric Maps (GIMs) and tropospheric zenith path delays, which are produced by, e.g., the International GNSS Service (IGS). For both dual- and triple-frequency Precise Point Positioning (PPP) processing, the significance of GIM and tropospheric products in processing is not obvious in the quality of the solution after a few hours. However, constraining the atmosphere improves PPP initialization and solution convergence in the first few minutes of processing. The general research question to be answered is whether there is any significant benefit in constraining the atmosphere in multi-frequency PPP? A key related question is: regarding time and position accuracy, how close are we to RTK performance in the age of multi-GNSS PPP-AR? To address these questions, this paper provides insight into the conceptual analyses of atmospheric GNSS PPP constraints. Dual- and triple-frequency scenarios were investigated. Over 60% improvement in convergence time was observed when atmospheric constraints are applied to a dual-frequency multi-GNSS PPP-AR solution. Future work would involve employing the constraints to improve low-cost PPP solutions.

scholarly journals On the Choice of the Third-Frequency Galileo Signals in Accelerating PPP Ambiguity Resolution in Case of Receiver Antenna Phase Center Errors

2020 ◽  
Vol 12 (8) ◽  
pp. 1315
Author(s):  
Shaoming Xin ◽  
Jianghui Geng ◽  
Jiang Guo ◽  
Xiaolin Meng
Keyword(s):  
Ambiguity Resolution ◽  
Convergence Time ◽  
Gps Receiver ◽  
Dual Frequency ◽  
International Gnss Service ◽  
Phase Center ◽  
Triple Frequency ◽  
Antenna Phase ◽  
Signal Combination ◽  
Antenna Phase Center

Rapid precise point positioning ambiguity resolution (PPP-AR) is of great importance to improving precise positioning efficiency. There is an expectation that Galileo multi-frequency (three or more frequencies) data processing will offer a promising way to accelerate PPP-AR. However, the performance of different combination observables out of raw Galileo multi-frequency data is still unclear, and the adverse impacts of missing receiver antenna phase center corrections have not been quantified in detail. We therefore studied uncombined Galileo PPP-AR by contrasting three typical triple-frequency combinations, which are E1/E5a/E5b, E1/E5a/E6, and E1/E5/E6 signals, using 30 days of data from 15 stations across Australia. We carried out triple-frequency PPP-AR by separately applying the official GPS receiver antenna phase centers, as currently employed in most relevant literatures, as well as the pilot Galileo receiver antenna phase centers preliminarily measured by the International GNSS Service. We found that, compared to dual-frequency (E1/E5a) PPP-AR, triple-frequency PPP-AR based on E1/E5a/E5b signals shortened the convergence time by only 7.6%, while those based on E1/E5a/E6 and E1/E5/E6 increased unexpectedly the convergence time by 17.6% and 12.7%, respectively, if the GPS receiver antenna corrections were presumed for Galileo signals. However, after using the pilot Galileo phase center corrections, triple-frequency PPP-AR based on E1/E5a/E5b, E1/E5a/E6, and E1/E5/E6 signals could speed up the convergence on average by about 16.2%, 30.3%, and 17.7%, respectively. Therefore, we demonstrate the critical impact of correct Galileo receiver antenna phase centers on multi-frequency PPP-AR convergences. Moreover, the triple-frequency signal combination E1/E5a/E6 is advantageous over others in achieving rapid triple-frequency Galileo PPP-AR.

scholarly journals Metrological Challenges in Collaborative Sensing: Applicability of Digital Calibration Certificates

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4730
Author(s):  
Tuukka Mustapää ◽  
Pekka Nikander ◽  
Daniel Hutzschenreuter ◽  
Raine Viitala
Keyword(s):  
Low Cost ◽  
Industrial Applications ◽  
Digital Calibration ◽  
Self Calibration ◽  
Chain Link ◽  
Calibration Methods ◽  
Collaborative Sensing ◽  
Future Work ◽  
Metrology Infrastructure

IoT systems based on collaborative sensor networks are becoming increasingly common in various industries owing to the increased availability of low-cost sensors. The quality of the data provided by these sensors may be unknown. For these reasons, advanced data processing and sensor network self-calibration methods have become popular research topics. In terms of metrology, the self-calibration methods lack the traceability to the established measurement standards of National Metrology Institutes (NMIs) through an unbroken chain-link of calibration. This problem can be solved by the ongoing digitalization of the metrology infrastructure. We propose a conceptual solution based on Digital Calibration Certificates (DCCs), Digital SI (D-SI), and cryptographic digital identifiers, for validation of data quality and trustworthiness. The data that enable validation and traceability can be used to improve analytics, decision-making, and security in industrial applications. We discuss the applicability and benefits of our solutions in a selection of industrial use cases, where collaborative sensing has already been introduced. We present the remaining challenges in the digitization and standardization processes regarding digital metrology and the future work required to address them.

Precise Point Positioning Model Using Triple GNSS Constellations: GPS, Galileo and BeiDou

2016 ◽  
Vol 10 (4) ◽  
Author(s):  
Akram Afifi ◽  
Ahmed El-Rabbany
Keyword(s):  
Real Time ◽  
Urban Areas ◽  
Precise Point Positioning ◽  
Convergence Time ◽  
Dual Frequency ◽  
Post Processing ◽  
International Gnss Service ◽  
Time Service ◽  
System Bias ◽  
Point Positioning

AbstractThis paper introduces a comparison between dual-frequency precise point positioning (PPP) post-processing model, which combines the observations of three different GNSS constellations, namely GPS, Galileo, and BeiDou and real-time PPP model. A drawback of a single GNSS system such as GPS, however, is the availability of sufficient number of visible satellites in urban areas. Combining GNSS observations offers more visible satellites to users, which in turn is expected to enhance the satellite geometry and the overall positioning solution. However, combining several GNSS observables introduces additional biases, which require rigorous modelling, including the GNSS time offsets and hardware delays. In this paper, a GNSS post-processing PPPP model is developed using ionosphere-free linear combination. The additional biases of the GPS, Galileo, and BeiDou combination are accounted for through the introduction of a new unknown parameter, which is identified as the inter-system bias, in the PPP mathematical model. Natural Resources Canada’s GPSPace PPP software is modified to enable a combined GPS / Galileo / BeiDou PPP solution and to handle the newly inter-system bias. A total of four data sets at four IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the IGS-MGEX network are used to correct of the GPS, Galileo and BeiDou measurements. For the real-time PPP model the corrections of the satellites orbit and clock are obtained through the international GNSS service (IGS) real-time service (RTS). GPS and Galileo Observations are used for the GNSS RTS-IGS PPP model as the RTS-IGS satellite products are not available for BeiDou satellites. This paper provides the GNSS RTS-IGS PPP model using different satellite clock corrections namely: IGS01, IGC01, IGS01, and IGS03. All PPP models results of convergence time and positioning precision are compared to the traditional GPS-only PPP model. It is shown that combining GPS, Galileo, and BeiDou observations in a PPP model reduces the convergence time by 25 % compared with the GPS-only PPP model.

scholarly journals Approaching Global Instantaneous Precise Positioning with the Dual- and Triple-Frequency Multi-GNSS Decoupled Clock Model

2021 ◽  
Vol 13 (18) ◽  
pp. 3768
Author(s):  
Nacer Naciri ◽  
Sunil Bisnath
Keyword(s):  
Ambiguity Resolution ◽  
Ar Model ◽  
Convergence Time ◽  
Dual Frequency ◽  
Clock Model ◽  
Precise Positioning ◽  
Triple Frequency ◽  
Positioning Technique ◽  
Carrier Phase Ambiguity ◽  
Decoupled Clock Model

Precise Point Positioning (PPP), as a global precise positioning technique, suffers from relatively long convergence times, hindering its ability to be the default precise positioning technique. Reducing the PPP convergence time is a must to reach global precise positions, and doing so in a few minutes to seconds can be achieved thanks to the additional frequencies that are being broadcast by the modernized GNSS constellations. Due to discrepancies in the number of signals broadcast by each satellite/constellation, it is necessary to have a model that can process a mix of signals, depending on availability, and perform ambiguity resolution (AR), a technique that proved necessary for rapid convergence. This manuscript does so by expanding the uncombined Decoupled Clock Model to process and fix ambiguities on up to three frequencies depending on availability for GPS, Galileo, and BeiDou. GLONASS is included as well, without carrier-phase ambiguity fixing. Results show the possibility of consistent quasi-instantaneous global precise positioning through an assessment of the algorithm on a network of global stations, as the 67th percentile solution converges below 10 cm horizontal error within 2 min, compared to 8 min with a triple-frequency solution, showing the importance of having a flexible PPP-AR model frequency-wise. In terms of individual datasets, 14% of datasets converge instantaneously when mixing dual- and triple-frequency measurements, compared to just 0.1% in that of dual-frequency mode without ambiguity resolution. Two kinematic car datasets were also processed, and it was shown that instantaneous centimetre-level positioning with a moving receiver is possible. These results are promising as they only rely on ultra-rapid global satellite products, allowing for instantaneous real-time precise positioning without the need for any local infrastructure or prior knowledge of the receiver’s environment.

An Innovative Dual Frequency PPP Model for Combined GPS/Galileo Observations

2015 ◽  
Vol 9 (1) ◽  
Author(s):  
Akram Afifi ◽  
Ahmed El-Rabbany
Keyword(s):  
Unknown Parameter ◽  
Precise Point Positioning ◽  
Satellite System ◽  
Convergence Time ◽  
Dual Frequency ◽  
Solution Convergence ◽  
Accuracy Level ◽  
Satellite Geometry ◽  
Galileo Satellite ◽  
Time Offset

AbstractThis paper develops a new dual-frequency precise point positioning model, which combines GPS and Galileo observables. The addition of Galileo satellite system offers more visible satellites to the user, which is expected to enhance the satellite geometry and the overall PPP solution in comparison with GPS-only PPP solution. However, combining GPS and Galileo observables introduces additional biases, which require rigorous modelling, including the GPS to Galileo time offset, and Galileo satellite hardware delay. In this research, a GPS/Galileo ionosphere-free linear combination PPP model is developed. The additional biases of the GPS/Galileo combination are lumped and accounted for through the introduction of a new unknown parameter, inter-systems bias, in the PPP mathematical model. It is shown that a subdecimeter positioning accuracy level and 25% reduction in the solution convergence time can be achieved with the developed GPS/Galileo PPP model.

scholarly journals Research Article. Improved Dual Frequency PPP Model Using GPS and BeiDou Observations

2017 ◽  
Vol 7 (1) ◽  
pp. 1-8 ◽  
Author(s):  
A. Afifi ◽  
A. El-Rabbany
Keyword(s):  
Precise Point Positioning ◽  
Satellite Orbit ◽  
Convergence Time ◽  
Data Sets ◽  
Dual Frequency ◽  
Research Article ◽  
Solution Convergence ◽  
Satellite Geometry ◽  
System Bias ◽  
Time Offset

AbstractThis paper introduces a new dual-frequency precise point positioning (PPP) model, which combines GPS and BeiDou observations. Combining GPS and BeiDou observations in a PPP model offers more visible satellites to the user, which is expected to enhance the satellite geometry and the overall PPP solution in comparison with GPSonly PPP solution. However, combining different GNSS constellations introduces additional biases, which require rigorous modelling, including GNSS time offset and hardware delays. In this research, ionosphere-free linear combination PPP model is developed. The additional biases, which result from combining the GPS and BeiDou observables, are lumped into a new unknown parameter identified as the inter-system bias. Natural Resources Canada’s GPSPace PPP software is modified to enable a combined GPS/BeiDou PPP solution and to handle the newly introduced biases. A total of four data sets at four IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the IGS-MGEX network are used to correct both of the GPS and BeiDou measurements. It is shown that a sub-decimeter positioning accuracy level and 25% reduction in the solution convergence time can be achieved with combining GPS and Bei-Dou observables in a PPP model, in comparison with the GPS-only PPP solution.

scholarly journals Performance Analysis of Several GPS/Galileo Precise Point Positioning Models

2021 ◽  
Author(s):  
Akram Afifi ◽  
Ahmed El-Rabbany
Keyword(s):  
Precise Point Positioning ◽  
Convergence Time ◽  
Data Sets ◽  
Dual Frequency ◽  
Clock Model ◽  
Solution Convergence ◽  
Single Difference ◽  
Point Positioning ◽  
Galileo Satellite ◽  
Decoupled Clock Model

This paper examines the performance of several precise point positioning (PPP) models, which combine dual-frequency GPS/Galileo observations in the un-differenced and between-satellite single-difference (BSSD) modes. These include the traditional un-differenced model, the decoupled clock model, the semi-decoupled clock model, and the between-satellite single-difference model. We take advantage of the IGS-MGEX network products to correct for the satellite differential code biases and the orbital and satellite clock errors. Natural Resources Canada’s GPSPace PPP software is modified to handle the various GPS/Galileo PPP models. A total of six data sets of GPS and Galileo observations at six IGS stations are processed to examine the performance of the various PPP models. It is shown that the traditional un-differenced GPS/Galileo PPP model, the GPS decoupled clock model, and the semi-decoupled clock GPS/Galileo PPP model improve the convergence time by about 25% in comparison with the un-differenced GPS-only model. In addition, the semi-decoupled GPS/Galileo PPP model improves the solution precision by about 25% compared to the traditional un-differenced GPS/Galileo PPP model. Moreover, the BSSD GPS/Galileo PPP model improves the solution convergence time by about 50%, in comparison with the un-differenced GPS PPP model, regardless of the type of BSSD combination used. As well, the BSSD model improves the precision of the estimated parameters by about 50% and 25% when the loose and the tight combinations are used, respectively, in comparison with the un-differenced GPS-only model. Comparable results are obtained through the tight combination when either a GPS or a Galileo satellite is selected as a reference.

Ionosphere VTEC modeling with the raw-observation-based PPP model：an advantage demonstration in the multi-frequency and multi-GNSS context

2020 ◽  
Author(s):  
Teng Liu ◽  
Baocheng Zhang ◽  
Yunbin Yuan ◽  
Xiao Zhang
Keyword(s):  
Rapid Development ◽  
Global Navigation Satellite Systems ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Dual Frequency ◽  
International Gnss Service ◽  
Total Electron ◽  
Satellite Systems ◽  
Triple Frequency ◽  
Global Navigation Satellite

<p>The ionospheric delay accounts for one of the major errors that the Global Navigation Satellite Systems (GNSS) suffer from. Hence, the ionosphere Vertical Total Electron Content (VTEC) map has been an important atmospheric product within the International GNSS Service (IGS) since its early establishment. In this contribution, an enhanced method has been proposed for the modeling of the ionosphere VTECs. Firstly, to cope with the rapid development of the newly-established Galileo and BeiDou constellations in recent years, we extend the current dual-system (GPS/GLONASS) solution to a quad-system (GPS/GLONASS/Galileo/BeiDou) solution. More importantly, instead of using dual-frequency observations based on the Carrier-to-Code Leveling (CCL) method, all available triple-frequency signals are utilized with a general raw-observation-based multi-frequency Precise Point Positioning (PPP) model, which can process dual-, triple- or even arbitrary-frequency observations compatibly and flexibly. Benefiting from this, quad-system slant ionospheric delays can be retrieved based on multi-frequency observations in a more flexible, accurate and reliable way. The PPP model has been applied in both post-processing global and real-time regional VTEC modeling. Results indicate that with the improved slant ionospheric delays, the corresponding VTEC models are also improved, comparing with the traditional CCL method.</p>

scholarly journals Estimation of GPS L2 Signal Observables Using Multilayer Perceptron Artificial Neural Networks for Positional Accuracy Improvement

2020 ◽  
Vol 24 (1) ◽  
pp. 97-103
Author(s):  
Cassio Vinícius Carletti Negri ◽  
Paulo Cesar Lima Segantine
Keyword(s):  
Multilayer Perceptron ◽  
Low Cost ◽  
Location Based Services ◽  
Global Navigation Satellite Systems ◽  
Dual Frequency ◽  
Positional Accuracy ◽  
Geospatial Information ◽  
Satellite Systems ◽  
Artificial Neural

In recent decades, due to the increasing mobility of people and goods, the rapid growth of users of mobile devices with location-based services has increased the need for geospatial information. In this context, positioning using data collected by the Global Navigation Satellite Systems (multi-GNSS) has gained more importance in the field of geomatics. The quality of the solutions is related, among other factors, to the receiver’s type used in the work. To improve the positioning with low-cost devices and to avoid additional user expenses, this work aims to propose the implementation of an Artificial Neural Network (ANN) to estimate the GPS L2 carrier observables. For this, a network model was selected through the cross-validation (CV) technique, the observations were estimated, and the accuracy of the solutions was analyzed. The CV technique demonstrated that a Multilayer Perceptron with four intermediate layers and one with one intermediate layer are the most appropriate configurations for this problem. The dual-frequency RINEX processing (with artificial data) revealed significant improvements. For some tests, it was possible to comply with the rural property georeferencing regulations of the Brazilian National Institute of Colonization and Agrarian Reform (INCRA). The results indicate, therefore, that the methodological proposal of the present investigation is very promising for approximating the quality of positioning reachable using a dual-frequency receiver.

scholarly journals Enhanced model for precise point positioning with single and dual frequency GPS/Galileo observables

2014 ◽  
Vol XL-2 ◽  
pp. 173-177 ◽  
Author(s):  
A. Afifi ◽  
A. El-Rabbany
Keyword(s):  
Urban Areas ◽  
Precise Point Positioning ◽  
Convergence Time ◽  
Dual Frequency ◽  
Estimation Model ◽  
Solution Convergence ◽  
Satellite Geometry ◽  
System Bias ◽  
Point Positioning ◽  
Time Offset

This paper introduces a newly developed model for both single and dual-frequency precise point positioning (PPP), which combines GPS and Galileo observables. As is well known, a drawback of a single GNSS system is the availability of sufficient number of visible satellites in urban areas. Combining GPS and Galileo systems offers more visible satellites to users, which is expected to enhance the satellite geometry and the overall positioning solution. However, combining GPS and Galileo observables introduces additional biases which require rigorous modelling, including the GPS to Galileo time offset (GGTO) and the inter-system bias. This research introduces a new ionosphere-free linear combination model for GPS/Galileo PPP, which accounts for the additional errors and biases. An additional unknown is introduced in the least-squares estimation model to account for the additional biases of the GPS/Galileo PPP solution. It is shown that a sub-decimeter level positioning accuracy and 20% reduction in the solution convergence time can be achieved with the newly developed GPS/Galileo PPP model.

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