Ionospheric propagation simulation tool with improved disturbances

Ionospheric propagation simulation tool with improved disturbances modelling with application to GNSS navigation and Earth observation

6th International Colloquium on Scientific and Fundamental Aspects of GNSS/Galileo

Ionospheric propagation simulation tool with improved disturbances modelling with application to GNSS navigation and Earth observation Adriano Camps1, José Barbosa2, Jose Miguel Juan1, Estefania Blanch3, David Altadill3, Guillermo Gonzalez1, Jaume Riba1, Gregori Vazquez1, Raul Orus4 1Universitat

Politècnica de Catalunya - Barcelona Tech (Barcelona, Spain) 2RDA (Zurich, Switzerland) 3Observatori de l’Ebre (Tarragona, Spain) 4ESA/ESTEC (Noordwijk, The Netherlands)

October 25-27, 2017, Valencia, Spain

Su

© UPC/OE/RDA/ESA, 2017

Braunschweig, October 25-27, Germany. 2017, Valencia, 27 - 29 October Spain 2015

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Outline: 1. Morphology of Ionospheric Scintillations 2. Scintillation Theory 3. UPC/OE/RDA Model Definition

4. Validation Tests 5. Impact on GNSS-R 6. Conclusions



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1. Morphology of Ionospheric Scintillations • Equatorial region: . ±20 of latitude of the magnetic equator . after sunset, pre-midnight period . Large (~100 km) depleted ionization volume driven through the F region, leaving a plume of small-scale (tens of cm to m) irregularities surrounding the depletion, which can extend through F-layer peak. . Produced by convective plasma processes . Irregularities with this range of scales are not independent from larger-scale plasma structures to those of smaller-scale irregularities.

• High latitude region: . From high-latitude edge of Van Allen outer belt into polar region . Lager occurrence during dark months, at all local times . Auroral zones: observed during nighttime period

• Mid latitudes: . All other regions . Extension of phenomenon at equatorial and auroral latitudes . Intense sporadic E layer at daytime October 25-27, 2017, Valencia, Spain


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2. Scintillation Theory Models using in situ data: 1. Basu et al. Equatorial Scintillation Model (1976): VHF, weak scintillation… 2. Basu High-Latitude Scintillation Models (1981): Northern winter, sunspot min. 3. WAM Model (2007): sunspot number 80–140, isotropic irregularities (S4), IRI…

Analytical Models: 1. Model of Fremouw and Rino (1973): 1st analytical model of scintillations, Foundation of WBMOD 2. Aarons Model (1985) 3. Franke and Liu Model (1985): equatorial latitudes, VHF to C-band … 4. Iyer et al. Model (2006): Scintillation occurrence index… 5. Retterer Model (2010): Phase screen formula accurate only for weak scattering, saturation of S4 imposed on the phase screen results.

Global Climatological Models: 1. WBMOD (WideBand MODel): activity lower than observed and ceases ~2 h earlier 2. GISM: same behavior for scintillations at different LT, only intensity changes.  Neither WBMOB, nor GISM show patchy character of equatorial scintillations October 25-27, 2017, Valencia, Spain


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3. UPC/OE/RDA Model Definition (i) Few ionospheric scintillation models are applicable to irregularities in realistic large structures such as equatorial bubbles and polar patches. • Low Frequency (slow) models: b1. TEC Background (NeQuick…) b2. TEC Stochastic Variations b3. Bubbles and Depletions Modelling

• High Frequency (fast) models: a1. High Latitude Scintillation Model a2. Low Latitude Scintillation Model



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3. UPC/OE/RDA Model (ii): Low & High frequency ionospheric effects Low-frequency effects

b2

Receiver Conﬁguration Parameters Constellation Data, Receiver Position and Date

User

b3

Stochastic TEC Variability Model Parameters

Bubbles and Depletions Model Parameters

Receiver & Satellite Position, Receiver Parameters

Receiver & Satellite Position, Receiver Parameters

Geometry Module

b1

(b) Algorithms

Nominal Conditions Ionospheric model (IONEX IGS)

(b2) Stochastic TEC Variability Model

(b3) Bubbles and Depletions Simulation

STEC

Perturbed STEC

Perturbed STEC

+

Receiver & Satellite Position, Receiver Parameters, Reference C/N0

+

Amplitude and Range Computation

+ C/N0 and Apparent Range, R(t)

Disturbed C/N0(t), R(t)

GNSS Receiver Simulator

Data Analysis

(a) Algorithms

a1 Scintillation Model Parameters Database

(a1) High Latitude Scintillation Effects (MPS)

S4 and Sigma_Phi

Scintillation Physical Model (Cornell)

a2

(a2) Low Latitude Scintillation Effects (MPS)

S4 and Sigma_Phi

Amplitude and Phase Disturbances (Delta_C/N0 and Delta_Phi)

Data

RINEX Files

Processing Algorithms

Impact in Localization Accuracy

Parameters

High-frequency effects October 25-27, 2017, Valencia, Spain


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3. UPC/OE/RDA Model Definition (iii)

b1. Low Frequency (slow) models: Background TEC • TEC Parametric Model (e.g. IRI, NeQuick, or inferred from GNSS networks) • TEC Stochastic Variations (random variations over parametric models)

http://swe.ssa.esa.int/web/guest/ism-public



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3. UPC/OE/RDA Model Definition (iv) b2. Low Frequency (slow) models: TEC Stochastic Variations • After UPC/gAGE study, PDF of TEC variability can be described approximately by a Gaussian distribution • TEC variability standard deviation (𝜎𝑉 ) and the average (typical) value ( 𝑉 ) depend on: year within solar cycle, month, LT, latitude, nominal TEC, and time frequency of perturbed geomagnetic conditions within the given month.

FAAS

TEC < 0.1 TECU is set 0.1 TECU

YELL



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3. UPC/OE/RDA Model Definition (v) b3. Bubbles and Depletions (iii)

World Geomagnetic Model World Geomagnetic Model Declination Inclination

Speed vectors of sample bubbles realizations

• Bubble probability x 10 • Generation Westwards as UT increases (LT constant) • Travel along iso-MODIP lines • Bubbles shape= Gaussian • Orientation along declination of geomagnetic field • Aspect ratio MODIP-dependent: AR= 4, |MODIP|≤10°, AR= 5, 10°1.2 TECUs/min)

ROTI fluctuations for large AATR values October 25-27, 2017, Valencia, Spain

• ROTI offset ~ 0.4 TECUs/min © UPC/OE/RDA/ESA, 2017

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3. UPC/OE/RDA Model Definition (viii) a1. Refractive Scintillation Model: High & Low Latitudes (ii) • Phase time series to be computed satisfying  and a spectrum that matches the experimental one. High latitudes

Pdf of slope spectrum dependent on 

Low latitudes

Pdf of slope spectrum Independent on 

Measured pdf of the slope (p) of the phase spectra measured at KIR1 receiver for different levels of scintillation (sigma_phi: [0, 0.3], (0.3, 0.5], (0.5, 0.7], (0.7, 0.9], (0.9, )) October 25-27, 2017, Valencia, Spain

Measured pdf of the slope (p) of the phase spectra measured at FAAS receiver for different levels of scintillation (sigma_phi: [0, 0.3], (0.3, 0.5], (0.5, 0.7], (0.7, 0.9], (0.9, ))


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3. UPC/OE/RDA Model Definition (ix)

a2. Diffractive Scintillation Model: Low Latitudes (i) •

Extension of Cornell Model

“Issues”

𝑚 = ma x( 0.6,1 𝑆42 𝐾= 𝑧=

𝑚2

−𝑚

𝑚 − 𝑚2 − 𝑚 2𝜎 2 · 𝐾

𝑧(𝑡 = 𝑧 + 𝜉(𝑡 𝑍(𝑡 = 𝑧 + 𝜉(𝑡 𝛼=

𝑧(𝑡

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Humphreys Ph D Thesis, [RD.22], referring to fig. above: “At S4 = m = 1, the Nakagami-m and Rice distributions both converge to the Rayleigh distribution. For S4 > 1, the Nakagami-m distribution is defined whereas the Rice distribution is not. (…) At values of S4 less than unity, the Nakagami-m and Rice distributions are similar, as illustrated in Fig. 2.1, where the two distributions are shown to agree closely with with a histogram (thick solid line) of representative Wideband UHF data from the scintillation library. However, for intermediate values of the perturbation strength of the screen (defined by the parameter Cs in [RD.21]), that is, perturbation strength values which lead to 1 > S4 > 0:6, the phase screen model tends to produce scintillation time histories whose amplitude distributions depart markedly from empirical amplitude distributions, as illustrated in Fig. 2-6.” © UPC/OE/RDA/ESA, 2017

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3. UPC/OE/RDA Model Definition (x)

a2. Diffractive Scintillation Model: Low Latitudes (ii) “More Issues” 2. Tends to produce correlated scintillation patterns at different frequencies as S4  0 (while correlation should tend to 0!!)

L1/L2 (blue), L1/L5 (red), and L2/L5 (orange) intensity correlations versus L1 S4 (from [RD.23])

Solution: generation of pairs of uncorrelated random variables and compute a new one as a linear combination of the previous two to achieve the desired correlation coefficient. October 25-27, 2017, Valencia, Spain


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3. UPC/OE/RDA Model Definition (xi)

a2. Diffractive Scintillation Model: Low Latitudes (iii) “More Issues” 3. At low latitudes, the diffractive scintillation effect seems to be enhanced by the presence of bubbles and depletions

Sample measurements showing an increase of the scintillation when bubbles and depletions occur. Note: S4 and  as predicted by GISM exhibit a very smooth temporal and geographical dependence that does not capture bubbles or EPBs October 25-27, 2017, Valencia, Spain


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4. Validation tests (i)

Sample simulation results for strong scintillation: S4 = 0.5,  = 3.14, and AATR = 0.2

L5

L2

L1

E5b

E5a

E1

Delta C/N0 [dB-Hz] 20 0 -20

20 0 -20

20 0 -20

50 0 -50

20 0 -20

50 0 -50

0

0

0

0

0

0

20

20

20

20

20

20

40

60

40

60

40

60

40

60

40

60

40

60

Delta Range [m]

80

80

80

80

80

80

100

100

100

100

100

100

20 15 10

40 30 20

40 30 20

-10 -20 -30

-20 -30 -40

-20 -40 -60

0

50

100

150

200

0

50

100

150

200

0

50

100

150

200

0

50

100

150

200

0

50

100

150

200

0

50

100 Time [s]

150

200

Time [s]



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4. Validation tests (ii) High Latitudes, Sigma-Phi frequency dependence Real Data Simulated Data KIR1 (Kiruna) Year: 2015, day 133 and time: 22:00

SPT0 (Sweden) Year: 2015, day 105 and time: 07:30

Frequency dependence of  follows very closely the real data in the refractive case. Note the SPT0 case, for an almost undisturbed case – in the real data almost no dependence is found as all

 values are close to 0.



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4. Validation tests (iii)

GNSS Outputs (GRANADA SW receiver),  Real Data

Simulated Data

KIR1 (Kiruna) Year: 2015, day 133 and time: 22:00 (ISMR)

SPT0 (Sweden) Year: 2015, day 105 and time: 07:30

Shape and frequency of disturbed phase matches very well, as well as the amplitude.



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4. Validation tests (iv)

GNSS Outputs (GRANADA SW receiver),  Real Data

Simulated Data

FAAS (Tahiti) Year: 2014, day 83 and time: 10:20 (ISMR)

KOUR (French Guiana) Year: 2014, day 57 and time: 00:30

Shape and frequency of disturbed phase matches very well, as well as the amplitude. Note the high frequency disturbances generated by the diffractive scintillation term. October 25-27, 2017, Valencia, Spain


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4. Validation tests (v) Bubbles and depletions model STEC Disturbance Temporal Cut

STEC Disturbance Spatial Map

PIMO (Philippines) Year: 2002 Winter, Day 9 Time: 16:00, Depth = -12.44 TECUs Duration = 25 min

MAL2 (Kenya) Year: 2014 Winter, Day 34 Time: 18:08 Depth = -11.12 TECUs Duration 20 min Both bubbles are well matched. Bubble orientation changing with MODIP iso-line direction October 25-27, 2017, Valencia, Spain


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4. Validation tests (vi)

Bubbles and depletions model Real Data

Simulated Data

KOUR (French Guiana) Year: 2014, day 83 and time: 03:30

Bubble pass increases the amplitude scintillation and this effect is correctly modeled in SCIONAV. Coupling factor is a configurable parameter for the simulation. October 25-27, 2017, Valencia, Spain


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5. Impact on GNSS-R •

SCATTEROMETRY: Increase of the Noise-to-Signal Ratio (linear units) as a function of the scint. parameter S4. Solid line: numerically simulated NSR, dotted line: polynomial fit. • Standard deviation of the measured 𝚫𝑵𝑺𝑹 = 𝟎. 𝟕𝟏 · 𝑺𝟑𝟒 − 𝟎. 𝟔 · 𝑺𝟐𝟒 + 𝟎. 𝟖𝟖 · 𝑺𝟒 . signal-to-noise ratio [dB] coincident with ASCAT A/B U10 data.

𝟏 𝑺𝑵𝑹

= 𝑺𝑵𝑹

𝟏 𝒏𝒐 𝒔𝒄𝒊𝒏𝒕𝒊𝒍𝒍𝒂𝒕𝒊𝒐𝒏

+ 𝚫𝑵𝑺𝑹.

• ALTIMETRY: Residual rms error of the ionosphere-free combination in the presence of diffractive scintillation computed with the UPC/OE/RDA SCIONAV model October 25-27, 2017, Valencia, Spain


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6. Conclusions • UPC/OE/RDA Model corrects some deficiencies in GISM: polar caps and 3D model not yet implemented • GNSS-R observations must be performed at the equator when no S4 exists (i.e. not from LT ~20 to 24 h) • Scatterometric and Altimetric observables under medium-strong ionospheric scintillation are significantly degraded (rms error in previous slide adds quadratically to other error sources): GEROS-ISS Error Budget (without ionosphere scintillation): Altimetry rms error estimated by combining L1/E1 and L5/E5 bands to correct for the ionospheric delay at nadir and at an incidence angle of 35 (swath edge)



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