Mitigation of Ionospheric Scintillation Effects for Precise GNSS Positioning - PDF Document

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  1. Mitigation of Ionospheric Scintillation Effects for Precise GNSS Positioning Dr Sreeja Vadakke Veettil International School of Space Science L’Aquila 19 September 2018 Sreeja.Veettil@nottingham.ac.uk

  2. Global Navigation Satellite Systems (GNSS) Satellite navigation systems that provide autonomous geo-spatial positioning with global coverage

  3. GNSS High Accuracy Applications

  4. Fundamentals of GNSS threats

  5. GNSS and the Ionosphere Earth’s ionosphere: Single largest error source in GNSS positioning error budget Ionospheric effects on GNSS signals

  6. Ionospheric Scintillation Phenomenon Rapid fluctuations in the amplitude and phase of transionospheric radio signals Basu, S. et al., J. Atmos. Terr. Phys, v.64, pp. 1745-1754,2002

  7. How do we measure scintillation? Amplitude Scintillation index S4: Standard deviation of the received signal power normalized to the average signal power    I   2 2 I I  S 4   where I is the received intensity and <.> denotes ensemble average (over 60s of high rate data) Phase scintillation index   : Standard deviation of the phase measurements 2   where  is the carrier phase measurement

  8. GNSS Scintillation monitoring receivers High rate data sampling (50Hz) High quality oscillator Record amplitude and phase scintillation indices The pioneer NovAtel GSV4004 receiver (late 1990’s) GPS only Now replaced by the NovAtel GPStation-6TM Multi-constellation multi-frequency Now replaced by the PolaRx5S

  9. Scintillation monitoring networks Brazil Europe Canada (CHAIN) (CIGALA/CALIBRA)

  10. Scintillation effects on GNSS receivers (1) Significantly degrade GNSS receiver tracking performance Code and phase tracking loop performances can be degraded Amplitude scintillation  signal-to-noise ratio decreases below the receiver threshold  signal loss and cycle slips Scintillating signals enter GNSS Rx tracking loop Phase scintillation  rapid phase shifts  exceed the loop bandwidth  loss of phase lock GNSS position errors

  11. Scintillation effects on GNSS receivers (2) Variance of the error at Delay Locked Loop / Phase Locked Loop output (tracking jitter) - good measure of scintillation effect on the receiver signal tracking Scintillation sensitive tracking error models: Conker et al. [2003] / Moraes et al. (2014)        2 2 2 2      S T osc Effect of scintillation Effect of thermal noise Effect of oscillator noise  .  1 B  T        2 1 n   2    2 L 2 L ( / ) 1 ( A 4 ) 2 ( / ) 1 ( A 2 4 ) c n S c n S    T 2 [ 1 ] k p S 0 1 / 1 0 1 / 1 L C L C  1 p sin kf n 2 k Conker et al., Radio Sci., doi: 10.1029/2000RS002604,2003 Moraes et al., Radio Science, v9(1), 2014

  12. Scintillation and Receiver Tracking Aquino and Sreeja, Space weather, doi:10.1002/swe.20047,2013;

  13. Scintillation x Positioning Errors Loss of lock on satellite – weaker geometry, large positioning errors, even outages Measurement quality degradation (large residuals) Positioning accuracy degradation (‘wrong’ coordinates)

  14. Loss of Lock correlated with scintillation Bronnoysund (~65oN) – GSV4004 Scintillation Monitor

  15. Impact of scintillation on positioning (1) Loss of lock on satellite >> weaker geometry >> even outages Position Dilution of Precision - PDOP

  16. Impact of scintillation on positioning (1a) High DOP values vary not only with the number of satellites being tracked Courtesy of M Lonchay

  17. Impact of scintillation on positioning (2) Measurement quality degradation >> large residuals All Satellites 08 Jun 1997 Low of the Solar Cycle 02 Apr 2001 Peak of the Solar Cycle (major Geomagnetic Storm)

  18. Impact of scintillation on positioning (3) Positioning accuracy degradation >> ‘wrong’ coordinates

  19. Impact on Tracking PRN15, L1C/A, PolaRxS@PresidentePrudente, Brazil, Sept 25, 2011 60 Amplitude scintillation [dB] Amplitude scintillation 50 (dB) 40 30 20 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Deep fade is the main problem for the PLL Time[hours] Phase scintillation [cycles] 0.5 Phase scintillation (cycles) 0 -0.5 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Time[hours] Courtesy of B Bougard

  20. Tracking level mitigation Standard lock detector Optimised lock detector Simulated scintillation (Cornell model - Spirent) L1 data bearing signals – GPS & Glonass 60 10 Loss-of-lock probability [%] Loss-of-lock probability [%] 50 8 40 6 30 4 20 2 10 0 0 20 20 1 1 15 15 0.8 0.8 10 10 0.6 0.6 5 5 Implemented in Septentrio receivers S4level 0.4 0.4 PLLbandwidth[Hz] PLLbandwidth[Hz] S4level Implemented in Septentrio receivers Courtesy of B Bougard

  21. However problem is transferred to PVT! 1.2 1 S4 from PRU2 [rad] 0.8 0.6 0.4 0.2 0 5.9 5.95 6 6.05 6.1 6.15 6.2 6.25 Height Error (m)

  22. Dilution of Precision (DOP) PDOP = 2.58 PDOP = 10.79 N N 0° 0° 30° 30° 60° 60° W E W E S S Courtesy of M Lonchay

  23. Effect of Satellite geometry PDOP = 4.39 PDOP = 152.05 N N N 0° 0° 0° 30° 30° 30° 60° 60° 60° W W E E W E Conical satellite geometry drives DOP to infinity!! S S S Courtesy of M Lonchay

  24. Least Squares stochastic model Usually w same constant weight for all satellite   w  1 t t ( ) ( ) x A WA A Wb w   W c I w

  25. Improve the LSQ stochastic model! Better w Apply different weights to individual satellites w While maintaining the same geometry!   W  1 t t ( ) ( ) x A WA A Wb w   W c I

  26. GNSS Positioning Solution Different weighting approaches: Satellite elevation angle Carrier to noise ratio (CN0) Receiver tracking error variances (Aquino et al. 2009) Inverse of the tracking error variances estimated per epoch per satellite Use scintillation indices and high rate (50 Hz) data Aquino et al., J. Geod., v.83, pp. 953-966,2009

  27. Ionospheric conditions Ny Alesund (79oN) - 30 October 2004; Kp reached 6 data courtesy of INGV Rome 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 -0.1 -0.2 -0.3 -0.4 -0.5 Aquino et al., J. Geod., v.83, pp. 953-966,2009

  28. Non-Mitigated Solution 1km baseline Ny Alesund (79oN) - 30 October 2004; Kp reached 6 data courtesy of INGV Rome 10 rms = 0.54m 8 6 4 2 height error (m) 0 -2 -4 -6 -8 -10 1 51 101 151 201 251 301 351 401 451 501 551 601 651 701 751 801 851 901 951 1001 1051 1101 1151 1201 1251 1301 1351 Minutes of the Day (30Oct04) Aquino et al., J. Geod., v.83, pp. 953-966,2009

  29. Mitigated Solution 1km baseline Ny Alesund (79oN) - 30 October 2004; Kp reached 6 data courtesy of INGV Rome 10 rms = 0.43 m 8 6 4 2 height error (m) 0 -2 -4 -6 -8 -10 1 51 101 151 201 251 301 351 401 451 501 551 601 651 701 751 801 851 901 951 1001 1051 1101 1151 1201 1251 1301 1351 Minutes of the Day (30Oct03) Aquino et al., J. Geod., v.83, pp. 953-966,2009

  30. Varying Baseline Solutions Baseline Length Average latitude Maximum Kp RMS w/o mitigation RMS with mitigation Height error improvement 1km ~79oN 6 0.54m 0.43m 21% 125km ~78oN 5 1.44m 0.90m 38% 511km ~52oN 6 1.52m 1.26m 17% 752km ~68oN 5 6.43m 5.32m 17% Aquino et al., J. Geod., v.83, pp. 953-966,2009

  31. Ionospheric conditions 125km baseline Ny Alesund/Longyearbean (~78oN) – data courtesy of INGV Rome Phi60 measured at station Nya1, 10 Dec 2006, 22-23UT 1.4 1.2 1 Phi60 (radians) 0.8 0.6 0.4 0.2 0 Time - 22-23UT of 10 December 2006 Aquino et al., J. Geod., v.83, pp. 953-966,2009

  32. Non-Mitigated Solution 125km baseline Ny Alesund/Longyearbean (~78oN) – data courtesy of INGV Rome Aquino et al., J. Geod., v.83, pp. 953-966,2009

  33. Mitigated Solution 125km baseline Ny Alesund/Longyearbean (~78oN) – data courtesy of INGV Rome Aquino et al., J. Geod., v.83, pp. 953-966,2009

  34. Mitigation Tool: Tracking Jitter variance maps Contour maps of verticalised tracking jitter to give overall tracking conditions Maps can assist users in estimating line of sight tracking conditions for different PLL configurations and signals Possible use to mitigate GNSS positioning errors Maps can be constructed over an area => users can estimate their slant jitter using a mapping function Sreeja et al., Space Weather, doi:10.1029/2011SW000707,2011

  35. Tracking Jitter variance maps Prikryl et al., Annals of Geophysics, doi:10.4401/ag-6219,2013

  36. Summary Growing reliance on GNSS for high accuracy positioning Ionospheric scintillation: serious problem for GNSS high accuracy positioning Effects range from degradation of accuracy to outages Scintillation leads to degradation in the GNSS receiver signal tracking performance Possible to improve signal tracking Bad data may remain and propagate into PVT solution Technique to mitigate scintillation effects on positioning An advanced stochastic model improves the positioning performance

  37. Further reading Aquino M, Monico JFG, Dodson AH, Marques H, De Franceschi G, Alfonsi L, Romano V, Andreotti M (2009) Improving the GNSS positioning stochastic model in the presence of ionospheric scintillation. J. Geod., 83: 953–966, doi:10.1007/s00190-009-0313-6 Aquino M, Sreeja V (2013) Correlation of scintillation occurrence with interplanetary magnetic field reversals and impact on Global Navigation Satellite System receiver tracking performance. Space Weather 11(5):219-224.doi:10.1002/swe.20047 Basu S, Groves KM, Basu Su, Sultan PJ (2002) Specification and forecasting of scintillations in communication/navigation links: current status and future plans. J Atmos Solar-Terr Phys 64(16):1745–1754. doi:https://doi.org/10.1016/S1364-6826(02)00124-4 Conker RS, El Arini MB, Hegarty CJ, Hsiao T (2003) Modeling the effects of ionospheric scintillation on GPS/SBAS availability. Radio Sci. 38(1). doi:10.1029/2000RS002604. Moraes AO, Costa E, de Paula ER, Perrella WJ, Monico JFG (2014) Extended ionospheric amplitude scintillation model for GPS receivers. Radio Sci 49(5):315-333. doi:10.1002/2013RS005307 Prikryl, P., Sreeja, V., Aquino, M. and Jayachandran, P. T. (2013), Probabilistic forecasting of ionospheric scintillation and GNSS receiver signal tracking performance at high latitudes, Annals of Geophysics, 56, 2, R0222; doi:10.4401/ag-6219. Sreeja V, Aquino M, Elmas ZG (2011b) Impact of ionospheric scintillation on GNSS receiver tracking performance over Latin America: Introducing the concept of tracking jitter variance maps. Space Weather 9(10):S10002.doi:10.1029/2011SW000707