Claudinei Rodrigues de AguiarFederal University of Technology - Parana

rodrigues.aguiar@gmail.com

Paulo de Oliveira Camargo São Paulo State University - UNESP

Real Time Ionosphere Maps from GNSS Active

Networks

Outline

• Introduction• Real time ionospheric modeling and

monitoring• Data Processing in Real Time• Experiments• Summary

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• GNSS has definitely been an important tool for observation of the atmosphere parameters, especially those from the ionosphere.

• Mod_Ion (Camargo, 1999) (1995 a 1999): for post processing applications was developed at FCT/UNESP;

• Kalman Filter was further implemented (Camargo, 2001);

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Introduction

• Mod_Ion_FK (Aguiar, 2005) - (2003 a 2005): Mod_Ion+Kalman Filter – changes in the functional model, and quality control was implemented in the Kalman filter algorithm;

• GNSS SP Network (2006): availability of real time data;

• GI e GIVE: current;

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Introduction

Introduction

• This work is part of a research project for atmospheric studies based on real time reference stations equipped with dual frequency GNSS receivers:

– GNSS SP (GNSS Active Network of São Paulo State)– RBMC (Brazilian Network for Continuous

Monitoring)

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Real time ionospheric modeling and monitoring

Two-dimensional

Analytical Models

Analytical functions Grid

Three-dimensional

Fourier seriesSpherical harmonics

Taylor series

Analytical functions

Empirical functions

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Bidimensional

Analytical Models

Analytical functions Grid

Tridimensional

Fourier seriesSpherical harmonics

Taylor series

Analytical functions

Empirical functions

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Real time ionospheric modeling and monitoring

• An ionospheric model has been developed for applications in real time;

• An algorithm based on a Kalman filter has been developed for ionosphere modeling at low latitudes and for the estimation of ionospheric parameters: absolute vertical TEC (VTEC);

• In this work we have utilized the two dimensional Fourier series for modeling the vertical ionospheric delay. However, other modeling functions are being implemented;

Real time ionospheric modeling and monitoring

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• The ionospheric delay values have been estimated from the geometry free linear combination of GPS dual frequency code-phase pseudorange smoothed by carrier phase observables (PS):

.1

drc

1

dscI)'z(sf

1

)PS(PS PsPv

1sr

sr12

647,1)f/f( 22L1L

Real time ionospheric modeling and monitoring

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• The ionospheric delay values have been estimated from the geometry free linear combination of GPS dual frequency code-phase pseudorange smoothed by carrier phase observables (PS):

Real time ionospheric modeling and monitoring

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.1

drc

1

dsc

])B sin(i a)B cos(ia[

ha])h sin(i a)h cos(ia[Baa

)'z(sf1

)PS(PS PsP

4m

102ij1i

s1j

sj

s32*n

4n

12ij1i

s1j

sj

s21

sr

sr12

• Calculation of ionospheric delay for each IPP:

1

)drsc(d

1

)PS(PSI P

sP

sr12s

r 1

e3,01)el(sf

240/el2

2IFB

2PS2

i

GIVE

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Real time ionospheric modeling and monitoring

• The real time modeling of the ionosphere is performed using data collected by active GNSS reference stations in Brazil;

• GNSS SP Network (GNSS Active Network of São Paulo State), leaded by FCT/UNESP and financed by FAPESP (São Paulo Research Foundation);

Real time ionospheric modeling and monitoring

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• GNSS SP Network: Currently, eleven GNSS active stations providing data in real time

Real time ionospheric modeling and monitoring

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• RBMC-IP (Brazilian Network for Continuous Monitoring of GNSS), maintained by IBGE (Brazilian Institute of Geography and Statistics );

Real time ionospheric modeling and monitoring

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• RBMC-IP

Real time ionospheric modeling and monitoring

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• These networks provide their data via the Internet using Internet Protocol (NTRIP);

• The availability of GNSS data via the NTRIP protocol brings new perspectives in research related to modeling and/or monitoring of the ionosphere in real time;

Real time ionospheric modeling and monitoring

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• NTRIP was projected to disseminate differential data correction or other types of GNSS data to users, moving or still, by the Internet.

Real time ionospheric modeling and monitoring

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Kalman Filter

Post-processing Real Time

GNSS PositioningIonosphere

GNSS Navigation Ionosphere Monitoring

Data via FTPRBMC

GNSS SP Network

Data via NTRIPRBMC-IP

GNSS SP Network

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Data Processing in Real Time

Data Processing in Real Time

•In Brazil some reference estations are providing real time data (RBMC-IP and GNSS SP Network);•These stations are equipped with dual frequency GNSS receivers that use NTRIP transport protocol;

•The station receivers are directly connected to the Internet, and the collected data are sent to a central computer that manages and storages the data

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BNC

•Using a Ntrip Client program we can download these data into a computer (convert ed to RINEX);

•We developed a package of algorithms for reading RINEX files in real time and the processing these data ;

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Data Processing in Real Time

BNC

ALDAR

Kalman Filter

Ionosphere Model:

Fourier Series

a1, ..., a19, dss and drr

Ionosphere Monitoring

dss, drr

VTEC, ROT, IPP

Real time ionosphere maps

GMT

Graphic visualization maps

Data Processing in Real Time

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ALDAR make possible process the data supplied by the reference stations in real time

BNC

ALDAR

Kalman Filter

Ionosphere Model:

Fourier Series

a1, ..., a19, dss and drr

Ionosphere Monitoring

dss, drr

VTEC, ROT, IPP

Real time ionosphere maps

GMT

Graphic visualization maps

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Data Processing in Real Time

Grid Maps - Brazil

GIVEL1 Ionospheric Delay

• November 22, 2009;• Real time processing;• 29 NTRIP stations.

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Grid Maps – South America

GIVEL1 Ionospheric Dealy

• May 11, 2006;• Processing for Central and South America stations, simulating real time;• 52 stations.

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Surface Maps - Brazil

GIVEL1 Ionospheric Delay

VTEC and ROT Map generated near real time from Grid.

ROT MapVTEC Map

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Surface Maps – South America

GIVEL1 Ionospheric Delay

VTEC and ROT Map generated simulating real time.

ROT Map

VTEC Map

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Output File

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Output File GIVE map Grid Map

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• Analyze of the quality of ionospheric grid:

IGI versus IREFERENCE

IGI- IREFERENCE < εGIVE

Grid Quality

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IGI versus IREFERENCE

Grid Quality

IUEPP IDGrd_r2.5

Limite de erro

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• The results show a limitation of the use of GI for the period of high solar activity, due to low number of the reference stations wich, consequently, results in a low number of IPP available to the generation of GI;

• When the GI degraded the results we observed that: GIVE was’nt available;

GIVE was available but did’nt have a minimum of 3 IGPs;

Impact of the density of reference stations

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Dez/2001 Out/2003

• Temporal availability varies from 10% (2.4 h) to 90%(21.6 h);

• Average of 70% (16.8 h monitored / unmonitored 7.2 h);

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Impact of the density of reference stations

Impact Analysis of the distribution of reference stations in GI

• It was developed the algortihm GS (Grid Simulator);

• GS is responsible for analyzing the distribution of reference stations.

• It is a software package that have their own libraries and also uses the GMT  and ImageMagick libraries.

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• 29 stations (GNSS SP, RBMC-IP)

• 24 hours of data;

• 5º: coverage of 95% (22.8 h) in most of Brazil, the region under the influence SP GNSS coverage reaches 98% (23.5 h).

• 2,5º: 25% (6 hours) in the worst case, and 97% (23,3 h) in the best situation.

• 1º: the cell with better coverage (67% - 16 h); in other cell the coverage varies from 3% (0.7 h) to 50% (12 h).

5° x 5°

2,5° x 2,5°

1° x 1°

5° x 5°

2,5° x 2,5°

1° x 1°

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Impact Analysis of the distribution of reference stations in GI

• Considering the current configuration of the available networks in Brazil, the best results are obtained when using grids with spatial resolution greater than 2.5 °.

• In the modeling of the ionosphere in real time, the best results are to be expected in the southeast, because of the influence of GNSS SP network;

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Impact Analysis of the distribution of reference stations in GI

• Analysis of the average distance: Resolution 5ºx5º spacing of approx. 600 km

Resolution 2,5ºx2,5º spacing of approx. 250 km

Resolution 1ºx1º spacing of approx. 100 km

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Impact Analysis of the distribution of reference stations in GI

Summary• The development of real time ionospheric model is

under progress.

• Some problems of dynamic programming have to be

solved.

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Summary• The next step is to provide, near real time, the

ionospheric model coefficients and an ionospheric

grid to users.• Tests carried out in point positioning show that the

corrections provided by the GI should be used only when the GIVE is available;

• The software developed also use libraries of the GMT (Generic Map Tools) and Image Magick, both open source.

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Thank you for your attention!

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