Optimizing GNSS signals’ tracking under strong ionospheric ...is-cigala-calibra.fct.unesp.br/is/calibra/calibra... · Optimizing GNSS signals’ tracking under strong ionospheric

Optimizing GNSS signals’ tracking under

strong ionospheric scintillation in Brazil

using the CIGALA network, baseband data

and a software receiver

Workshop CALIBRA DAY, São Paulo, May 9, 2014

Luiz Paulo Souto Fortes IBGE/UERJ – Brazil

Scholar of CNPq

Tao Lin, Gérard Lachapelle University of Calgary - Canada

Contents

Introduction

• The 2013 Solar Maximum and its effects on GNSS signals

• Research objectives

Data collection and processing

Results in the observation and position domains

GSNRx™ features for tracking under scintillation

Conclusions

The

Solar

Cycles

The Solar Cycle 24

• Ionospheric delay

– Dependent on signal

frequency and level of

ionization (i.e., TEC)

Effects on GNSS signals

• Ionospheric scintillation

– Random rapid variations in the intensity and phase of the

received signals resulting from electron density irregularities in

the ionosphere

• CORS network

operated by IBGE

• 101 stations

(March 2014)

• Provide access to

SIRGAS2000

• More than 40,000

downloads per

month!

• To investigate the effects of the 2013 Solar Maximum on GNSS signals’ tracking, using:

– Baseband (i.e., Intermediate Frequency - IF) data collected by a front-end device at IBGE facilities in Rio de Janeiro

– GSNRx™ software receiver developed by the Position, Location and Navigation (PLAN) Group of the Department of Geomatics Engineering, University of Calgary, Canada

• To contribute to the development of robust GNSS signals’ tracking methods

• To study software receivers in order to evaluate their use in RBMC

Research objectives

GNSS Software receiver

Preamplifier Down

Converter IF Sampling

Reference

Oscillator

Frequency

Synthesizer

IF Signal

Processing

Navigation

Processing

Antenna

Local Oscillator

RF Front-End Signal Processing

Advantage of using a software receiver:

the flexibility of a software-based approach

Hardware

Software

• Baseband (IF) data collected from June 04 2012 to

March 29 2013, 8-12pm local time

– Suitable time period, as the peak of Solar Cycle 24 occurred in

September 2013, with a secondary peak in February 2012

Data collection

Data collection

RIOFE station (front-

end) located 5m from

RBMC RIOD station,

allowing performance

comparison

• 4-hour IF data file: 67GB (compressed!)

• Challenge: very difficult to predict scintillation

Data collection

Automaticaly

collect IF data

Check the CIGALA

website

Scintillation

occurence? Save the file

Yes Delete the file

No

Methodology

79 data files collected, 5.16TB in total!

Data collection

• 5 sessions selected for processing

– October 24 2012, November 17 2012, February 20 2013: under severe equatorial ionospheric scintillation

– March 28 2013: few satellites affected by scintillation

– June 04-05 2012: no scintillation, for comparison

Data processing

Amplitude scintillation S4 index

CIGALA SJCU station

Data processing

Data processing


CIGALA SJCU station

Data processing


CIGALA SJCU station

Data processing


CIGALA SJCU station

Data processing


CIGALA SJCU station

• Decompressing the 67GB session file

– Generates 2 files (for L1 and L2) with

268GB each

– At the beginning, this process took 8 hours;

with computer hardware improvements, the

processing time was reduced to 1h40m

• Processing the L1 and L2 session files

with GSNRx™

– At the beginning, it took around 29 hours;

with computer hardware and software

improvements, this time was reduced to

5 to 7 hours

Data processing

The final processing time of a 4-hour IF session file:

7 to 9h

• S4 computation using in-phase (I) and quadra-

phase (Q) accumulation results of the channel

correlators generated by GSNRx™

(SI = signal intensity)

Data processing

2

22

SI

SISIS4

Data processing S4 at RIOFE vs SJCU (350 km apart)

S4 vs C/No for PRN12 L1 C/A and L2CM signals

Data processing

Results in the observation domain

• Analysis of the GSNRx™ and RIOD Trimble NetRS

observations under ionospheric scintillation

– Cycle slip detection using the dual frequency method

– Missing GPS L2 phase observations,

for IIR-M e IIF satellites, as the GSNRx™ version

used in this research operated on L1 and L2C

signals (and not on L2P(Y))

thresholdΦΦΦΦ12 tL2L1tL2L1


Satellites (SV)

IIR-M/IIF

Missing L2

observations (%)

# of dual frequency

cycle slips

RIOFE RIOD RIOFE RIOD

05 16 17 0 22

12 0 5 0 47

15 2 20 0 23

25 0 1 0 3

29 1 18 0 60

31 3 22 0 27

Total for IIR-M

and IIF SV 4 11 0 182

Total for all

visible SV -- 13 -- 288

Session: October 24, 2012

(strong scintillation)

Session: November 17, 2012


Satellites (SV)

IIR-M/IIF

Missing L2

observations (%)

# of dual frequency

cycle slips


05 1 4 0 19

12 5 4 0 38

15 25 52 0 0

25 0 0 0 5

29 0 0 2 0

31 0 0 0 0

Total for IIR-M

and IIF SV 3 4 2 62

Total for all

visible SV -- 9 -- 146


Session: February 20, 2013


Satellites (SV)

IIR-M/IIF

Missing L2

observations (%)

# of dual frequency

cycle slips


01 0 5 0 2

31 7 8 0 2

Total for IIR-M

and IIF SV 4 7 0 4

Total for all



Session: March 28, 2013

(strong scintillation on fewer SV)

Satellites (SV)

IIR-M/IIF

Missing L2

observations (%)

# of dual frequency

cycle slips


01 0 0 0 0

07 14 27 0 0

31 0 0 0 0

Total for IIR-M

and IIF SV 1 2 0 0

Total for all



Satellites (SV)

IIR-M/IIF

Missing L2

observations (%)

# of dual frequency

cycle slips


05 0 0 0 0

07 0 0 0 0

17 0 8 0 0

Total for IIR-M

and IIF SV 0 2 0 0

Total for all


Session: June 04-05, 2012

(no scintillation)


RBMC receiver evolution since the previous Solar

maximum (2002)

Missing L2 observations (%) # of dual frequency cycle slips

RIOD – Trimble SSi – March 17 2002 (S4 0,95)

41 89

RIOD – Trimble NetRS – October 24 2012

13 288

UBA1 – Trimble NetR8 – October 24 2012 (200 km from RIOD)

7 125

RIOFE – GSNRx – October 24 2012 (5 m from RIOD)

(for IIR-M and IIF satellites only)

4 0


Results in the position domain

• Analysis of PPP positioning using GSNRx™ and RIOD

Trimble NetRS observations under ionopsheric

scintillation

– PPP services used:

• IBGE

• Natural Resources Canada (NRCan)

– Final results with NRCan-PPP

• L1 pseudorange kinematic solutions for the 5 selected days

• Code+phase dual frequency kinematic solutions require

enough epochs with L1, L2, C1 and C2/P2 observations for

4 to 5 satellites condition fulfilled on November 17, 2012


NRCan-PPP L1 pseudorange kinematic solutions











NRCan-PPP dual frequency (= iono.free) kinematic solutions


Station Type of PPP

Solution

Differences to known coordinates (m) A posteriori code std deviation

(m)

Latitude Longitude Height

RMS Mean RMS Mean RMS Mean

Session: October 24 2012 (strong scintillation) RIOFE L1 code 3,9 -2,1 3,8 3,1 7,9 -1,6 2,8

RIOD L1 code 4,2 -2,3 4,0 3,2 6,9 -1,3 2,9

Session: November 17 2012 (strong scintillation) RIOFE L1 code 3,2 -1,5 2,8 1,5 4,3 1,4 2,6

RIOD L1 code 3,3 -1,7 3,1 2,0 4,2 1,5 2,4

RIOFE

L1 L2 code (C/A and L2C)

and phase 0,16 0,15 0,07 -0,05 0,33 0,25 2,8

RIOD

L1 L2 code (C/A and L2P)

and phase 0,24 0,03 0,13 0,06 0,12 0,01 1,1

Session: February 20 2013 (strong scintillation) RIOFE L1 code 2,5 -1,6 2,2 1,8 3,8 2,1 2,1

RIOD L1 code 2,6 -1,6 2,1 1,7 4,2 2,2 2,0

Session: March 28 2013 (strong scintillation on fewer satellites) RIOFE L1 code 4,6 -3,6 2,0 1,3 8,1 5,8 2,2

RIOD L1 code 4,8 -3,8 1,8 1,4 8,2 5,8 2,0

Session: June 04-05 2012 (no scintillation) RIOFE L1 code 0,7 0,2 0,8 -0,4 1,9 -0,3 0,9

RIOD L1 code 0,4 0,2 0,3 -0,1 0,9 -0,2 0,5


GSNRx™ features for tracking under scintillation

• Data collected represented important and excellent sample to optimize tracking under scintillation

• Main features implemented on GSNRx™ – Tracking parameters

• Phase Lock Loop bandwith reduced from 15 to 3 Hz

• Delay Lock Loop bandwith reduced from 2.5 to 0,01 Hz

– Receiver architecture:

• From independent-channel architecture to shared-channel architecture, which utilizes the inter-channel aiding from channels and satellites for robust GNSS signal tracking under scintillation

• Results shown in this presentation have been generated using GSNRx™ optimized version

Conclusions

• Collection of important and unseen 5.16TB IF dataset

for GNSS signal acquisition and tracking research

• Evolution of RBMC geodetic receivers during the past

11 years, reducing the missing GPS L2 observations

by a factor of 3 to 6 improvement of the information

made available to users

• GSNRx™ flexibility has allowed optimizing acquisition

and tracking of GPS signals under severe scintillation

excellent performance, superior to RBMC receivers,

with only 4% of missing L2 observations and ZERO

cycle slips in all scenarios

Conclusions

• Current GNSS signals acquisition and tracking algorithms

are highly resistant to equatorial ionospheric scintillation

• Submission of GSNRx™ and Trimble NetRS observations to

the NRCan-PPP service generated similar results in the

position domain, with ionospheric delay being responsible

for degrading the coordinates’ accuracy by a factor up to 12

• The flexibility and potential of a software receiver justify the

need of closely following up the corresponding

technology/cost evolution in order to assess its use in

RBMC

Acknowledgements

• Mark Petovello, Fatemeh Ghafoori and James Curran, PLAN

Group of the Department of Geomatics Engineering, University of

Calgary

• Maria Cristina Barboza Lobianco, Sonia Maria Alves Costa,

Rodrigo Augusto Quirino e Alberto Luis da Silva, Coordination of

Geodesy - IBGE Directorate of Geosciences

• Mario Luiz Souto, Coordination of Technology - IBGE Directorate of

Information Technology

• Pierre Tétreault and the team responsible for the NRCan-PPP

service

• João Francisco Galera Monico, CIGALA and Unesp

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Optimizing GNSS signals’ tracking under strong ionospheric ...is-cigala-calibra.fct.unesp.br/is/calibra/calibra... · Optimizing GNSS signals’ tracking under strong ionospheric