scholarly journals Ionospheric Delay Handling for Relative Navigation by Carrier-Phase Differential GPS

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
A. Renga ◽  
U. Tancredi ◽  
M. Grassi
Keyword(s):  
Carrier Phase ◽  
Ionospheric Delay ◽  
Relative Positioning ◽  
Dual Frequency ◽  
Differential Gps ◽  
Gps Measurements ◽  
Long Baseline ◽  
Standard Solution ◽  
Gravity Recovery ◽  
Grace Mission

The paper investigates different solutions for ionospheric delay handling in high accuracy long baseline relative positioning by Carrier-Phase Differential GPS (CDGPS). Standard literature approaches are reviewed and the relevant limitations are discussed. Hence, a completely ionosphere-free approach is proposed, in which the differential ionospheric delays are cancelled out by combination of dual frequency GPS measurements. The performance of this approach is quantified over real-world spaceborne GPS data made available by the Gravity Recovery and Climate Experiment (GRACE) mission and compared to the standard solution.

Precise Spacecraft Relative Positioning using Single-Frequency Pseudorange Measurements

2008 ◽  
Vol 62 (1) ◽  
pp. 119-134 ◽  
Author(s):  
Marc-Philippe Rudel ◽  
Pini Gurfil
Keyword(s):  
Satellite Data ◽  
Carrier Phase ◽  
The Other ◽  
Single Frequency ◽  
Relative Positioning ◽  
Positioning Accuracy ◽  
Differential Corrections ◽  
Gravity Recovery ◽  
Grace Mission ◽  
Better Than

The ranging accuracy provided by pseudorange-only techniques is usually no better than a few metres when no differential corrections are applied. Carrier-phase algorithms, on the other hand, yield higher-precision estimates – down to a few millimetres – but are prone to ambiguities difficult to resolve. An easier-to-implement method, using single-frequency pseudorange measurements only, is presented. It allows for a decimetre-level relative positioning accuracy. Results, derived from the GPS Relative Positioning Equations, are validated with actual satellite data from the Gravity Recovery and Climate Experiment (GRACE) mission.

scholarly journals Integration of precise point positioning and reduced inertial sensors system

2021 ◽  
Author(s):  
Hassan E. Ibrahim
Keyword(s):  
Carrier Phase ◽  
Precise Point Positioning ◽  
Inertial Sensors ◽  
Position Estimation ◽  
Dual Frequency ◽  
Differential Gps ◽  
Static Mode ◽  
Land Vehicle ◽  
Frequency Code ◽  
Point Positioning

In Global Positioning System (GPS), Precise Point Positioning (PPP) achieves the highest accuracy in point positioning. It approaches centimetre-level accuracy in static mode and sub-decimetre accuracy in kinematic mode. PPP is an alternative approach to carrier-phase-based Differential GPS (DGPS) and offers advantages over DGPS. PPP uses GPS observations from a single receiver for position estimation, which is simpler than using more than one GPS receiver. However, PPP needs rigorous modelling for all errors and biases, which are otherwise cancelled out or mitigated when using DGPS. PPP’s popularity is on the rise, as it is ideal for land-vehicle positioning and navigation. However, in challenging environments, PPP suffers from a signal loss that prevent continuous navigation or a reduction in the number of visible satellites that causes accuracy degradation. This research integrates PPP with a Reduced Inertial Sensors System (RISS) — a low-cost system that uses data from reduced MEMS-based inertial sensors and vehicle odometry — to provide accurate and inexpensive land-vehicle navigation systems. The system is integrated in a tightly coupled mode through the use of an Extended Kalman Filter (EKF), which employs an improved error model for the RISS data. The system was tested using data from real driving routes with single-frequency code-based PPP/RISS (SF-code-PPP/RISS), dual-frequency code-based PPP (DF-code-PPP/RISS), smoothed dual-frequency code-based PPP (S-DF-code-PPP/RISS), and code- and carrier-phase-based PPP (code-carrier-PPP/RISS). The performance of the developed PPP/RISS was evaluated using position RMS and maximum errors during continuous GPS availability as well as during signal outages. The developed integrated algorithms were assessed using three real road tests that capture different navigational conditions. The results show that when five or more satellites are available, code-carrier-PPP/RISS solution is superior to that of SF- and DF-code-PP/RISS. For latitude, code-carrier-PPP/RISS solution was 47% and 20% more precise than the SF- and DF-code- PP/RISS counterparts, respectively. For longitude, code-carrier-PPP/RISS solution was 65% and 31% more precise than the SF- and DF-Code-PP/RISS counterparts, respectively. Similarly, the altitude solution was improved by 46% and 25%, respectively. During GPS signal outages of 60 seconds, code-carrier-PPP/RISS’s algorithms outperformed that of SF- and DF-code-PPP/RISS by about 35% when the satellite availability level was set to three satellites. For other satellite availability levels, the algorithms performed almost identically.

scholarly journals Vertical Ionosphere Delay Estimation using Zero Difference GPS Phase Observation

2018 ◽  
Author(s):  
Ahmed Elsayed ◽  
Ahmed Sedeek ◽  
Mohamed Doma ◽  
Mostafa Rabah
Keyword(s):  
Carrier Phase ◽  
Free Carrier ◽  
Error Modeling ◽  
Ionospheric Delay ◽  
Electron Content ◽  
Gps Receiver ◽  
Dual Frequency ◽  
Total Electron ◽  
Longitudinal Gradients ◽  
Least Squares Adjustment

Abstract. An apparent delay is occurred in GPS signal due to both refraction and diffraction caused by the atmosphere. The second region of the atmosphere is the ionosphere. The ionosphere is significantly related to GPS and the refraction it causes in GPS signal is considered one of the main source of errors which must be eliminated to determine accurate positions. GPS receiver networks have been used for monitoring the ionosphere for a long time. The ionospheric delay is the most predominant of all the error sources. This delay is a function of the total electron content (TEC). Because of the dispersive nature of the ionosphere, one can estimate the ionospheric delay using the dual frequency GPS. In the current research our primary goal is applying Precise Point Positioning (PPP) observation for accurate ionosphere error modeling, by estimating Ionosphere delay using carrier phase observations from dual frequency GPS receiver. The proposed algorithm was written using MATLAB. The proposed Algorithm depends on the geometry-free carrier-phase observations after detecting cycle slip to estimates the ionospheric delay using a spherical ionospheric shell model, in which the vertical delays are described by means of a zenith delay at the station position and latitudinal and longitudinal gradients. Geometry-free carrier-phase observations were applied to avoid unwanted effects of pseudorange measurements, such as code multipath. The ionospheric estimation in this algorithm is performed by means of sequential least-squares adjustment. Finally, an adaptable user interface MATLAB software are capable of estimating ionosphere delay, ambiguity term and ionosphere gradient accurately.

Vertical ionospheric delay estimation for single-receiver operation

2019 ◽  
Vol 13 (2) ◽  
pp. 81-91 ◽  
Author(s):  
Ahmed Elsayed ◽  
Ahmed Sedeek ◽  
Mohamed Doma ◽  
Mostafa Rabah
Keyword(s):  
Carrier Phase ◽  
Free Carrier ◽  
Error Modeling ◽  
Ionospheric Delay ◽  
Electron Content ◽  
Gps Receiver ◽  
Dual Frequency ◽  
Total Electron ◽  
Longitudinal Gradients ◽  
Least Squares Adjustment

Abstract An apparent delay is occurred in GPS signal due to both refraction and diffraction caused by the atmosphere. The second region of the atmosphere is the ionosphere. The ionosphere is significantly related to GPS and the refraction it causes in GPS signal is considered one of the main source of errors which must be eliminated to determine accurate positions. GPS receiver networks have been used for monitoring the ionosphere for a long time. The ionospheric delay is the most predominant of all the error sources. This delay is a function of the total electron content (TEC). Because of the dispersive nature of the ionosphere, one can estimate the ionospheric delay using the dual frequency GPS. In the current research our primary goal is applying Precise Point Positioning (PPP) observation for accurate ionosphere error modeling, by estimating Ionosphere delay using carrier phase observations from dual frequency GPS receiver. The proposed algorithm was written using MATLAB and was named VIDE program. The proposed Algorithm depends on the geometry-free carrier-phase observations after detecting cycle slip to estimates the ionospheric delay using a spherical ionospheric shell model, in which the vertical delays are described by means of a zenith delay at the station position and latitudinal and longitudinal gradients. Geometry-free carrier-phase observations were applied to avoid unwanted effects of pseudorange measurements, such as code multipath. The ionospheric estimation in this algorithm is performed by means of sequential least-squares adjustment. Finally, an adaptable user interface MATLAB software are capable of estimating ionosphere delay, ambiguity term and ionosphere gradient accurately.

scholarly journals Integration of precise point positioning and reduced inertial sensors system

2021 ◽  
Author(s):  
Hassan E. Ibrahim
Keyword(s):  
Carrier Phase ◽  
Precise Point Positioning ◽  
Inertial Sensors ◽  
Position Estimation ◽  
Dual Frequency ◽  
Differential Gps ◽  
Static Mode ◽  
Land Vehicle ◽  
Frequency Code ◽  
Point Positioning

In Global Positioning System (GPS), Precise Point Positioning (PPP) achieves the highest accuracy in point positioning. It approaches centimetre-level accuracy in static mode and sub-decimetre accuracy in kinematic mode. PPP is an alternative approach to carrier-phase-based Differential GPS (DGPS) and offers advantages over DGPS. PPP uses GPS observations from a single receiver for position estimation, which is simpler than using more than one GPS receiver. However, PPP needs rigorous modelling for all errors and biases, which are otherwise cancelled out or mitigated when using DGPS. PPP’s popularity is on the rise, as it is ideal for land-vehicle positioning and navigation. However, in challenging environments, PPP suffers from a signal loss that prevent continuous navigation or a reduction in the number of visible satellites that causes accuracy degradation. This research integrates PPP with a Reduced Inertial Sensors System (RISS) — a low-cost system that uses data from reduced MEMS-based inertial sensors and vehicle odometry — to provide accurate and inexpensive land-vehicle navigation systems. The system is integrated in a tightly coupled mode through the use of an Extended Kalman Filter (EKF), which employs an improved error model for the RISS data. The system was tested using data from real driving routes with single-frequency code-based PPP/RISS (SF-code-PPP/RISS), dual-frequency code-based PPP (DF-code-PPP/RISS), smoothed dual-frequency code-based PPP (S-DF-code-PPP/RISS), and code- and carrier-phase-based PPP (code-carrier-PPP/RISS). The performance of the developed PPP/RISS was evaluated using position RMS and maximum errors during continuous GPS availability as well as during signal outages. The developed integrated algorithms were assessed using three real road tests that capture different navigational conditions. The results show that when five or more satellites are available, code-carrier-PPP/RISS solution is superior to that of SF- and DF-code-PP/RISS. For latitude, code-carrier-PPP/RISS solution was 47% and 20% more precise than the SF- and DF-code- PP/RISS counterparts, respectively. For longitude, code-carrier-PPP/RISS solution was 65% and 31% more precise than the SF- and DF-Code-PP/RISS counterparts, respectively. Similarly, the altitude solution was improved by 46% and 25%, respectively. During GPS signal outages of 60 seconds, code-carrier-PPP/RISS’s algorithms outperformed that of SF- and DF-code-PPP/RISS by about 35% when the satellite availability level was set to three satellites. For other satellite availability levels, the algorithms performed almost identically.

scholarly journals A DSRC Doppler/IMU/GNSS Tightly-coupled Cooperative Positioning Method for Relative Positioning in VANETs

2016 ◽  
Vol 70 (1) ◽  
pp. 120-136 ◽  
Author(s):  
Feng Shen ◽  
Joon Wayn Cheong ◽  
Andrew G. Dempster
Keyword(s):  
Doppler Shift ◽  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Relative Positioning ◽  
Differential Gps ◽  
Gps Measurements ◽  
Cooperative Positioning ◽  
Tightly Coupled

Relative position awareness is a vital premise for the implementation of emerging intelligent transportation systems. However, commercial Global Satellite Navigation Systems (GNSS) receivers do not satisfy the requirements of these applications. Fortunately, Cooperative Positioning (CP) systems, based on inter-vehicle communications, have improved performance of relative positioning in a Vehicular Ad Hoc Network (VANET). CP techniques rely primarily on measurements from the Global Positioning System (GPS) to deliver measurements or positions that describe the location of individual vehicles. In urban environments, the reduced quality or complete unavailability of GPS measurements challenges the effectiveness of any CP algorithm. In this paper, a new enhanced tightly–coupled CP technique is presented by adding the measurements from low-cost inertial sensors and the Doppler shift of the carrier of Dedicated Short-Range Communications (DSRC) signals. In the enhanced CP method proposed here, vehicles communicate their Inertial Measurement Unit (IMU) data and GPS measurements. Each vehicle fuses the GPS measurements and IMU data and the inter-node range-rates based on the Doppler shift of the carrier of DSRC signals. Based on analytical and experimental results, in a full GPS coverage environment, the new tight integration CP outperforms tight CP with Inertial Navigation System (INS), tight CP and differential GPS by at least by 6%, 15%, and 28%, respectively. In a GPS outage, the performance improvement can be up to 60%, 55%, and 66% respectively.

scholarly journals Study of water storage variations at the Pantanal wetlands area from GRACE monthly mass grids

2019 ◽  
Vol 9 (1) ◽  
pp. 133-143
Author(s):  
Ayelen Pereira ◽  
Cecilia Cornero ◽  
Ana C. O. C. Matos ◽  
M. Cristina Pacino ◽  
Denizar Blitzkow
Keyword(s):  
Water Mass ◽  
Spatial Scales ◽  
Water Storage ◽  
Transport Processes ◽  
Satellite Gravity ◽  
The North ◽  
Paraguay River ◽  
Gravity Recovery ◽  
Grace Mission ◽  
Phase Differences

Abstract The continental water storage is significantly in-fluenced by wetlands, which are highly affected by climate change and anthropogenic influences. The Pantanal, located in the Paraguay river basin, is one of the world’s largest and most important wetlands because of the environmental biodiversity that represents. The satellite gravity mission GRACE (Gravity Recovery And Climate Experiment) provided until 2017 time-variable Earth’s gravity field models that reflected the variations due to mass transport processes-like continental water storage changes-which allowed to study environments such as wetlands, at large spatial scales. The water storage variations for the period 2002-2016, by using monthly land water mass grids of Total Water Storage (TWS) derived from GRACE solutions, were evaluated in the Pantanal area. The capability of the GRACE mission for monitoring this particular environment is analyzed, and the comparison of the water mass changes with rainfall and hydrometric heights data at different stations distributed over the Pantanal region was carried out. Additionally, the correlation between the TWS and river gauge measurements, and the phase differences for these variables, were also evaluated. Results show two distinct zones: high correlations and low phase shifts at the north, and smaller correlation values and consequently significant phase differences towards the south. This situation is mainly related to the hydrogeological domains of the area.

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