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Insensitivity of GNSS to geocenter motion through the network shift approach Paul Rebischung, Zuheir Altamimi, Tim Springer AGU Fall Meeting 2013, San Francisco, December 9-13, 2013 1

Observing geocenter motion with GNSS

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Insensitivity of GNSS to geocenter motion through the network shift approach Paul Rebischung, Zuheir Altamimi, Tim Springer AGU Fall Meeting 2013, San Francisco, December 9-13, 2013. Observing geocenter motion with GNSS. Degree-1 deformation approach (Blewitt et al., 2001): - PowerPoint PPT Presentation

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Page 1: Observing geocenter motion with GNSS

Insensitivity of GNSS to geocenter motion through the network shift approach

Paul Rebischung, Zuheir Altamimi, Tim Springer

AGU Fall Meeting 2013, San Francisco, December 9-13, 20131

Page 2: Observing geocenter motion with GNSS

Observing geocenter motion with GNSS

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• Degree-1 deformation approach (Blewitt et al., 2001):– Based on the fact that loading-induced geocenter motion is

accompanied by deformations of the Earth’s crust.– Gives satisfying results.– But can only sense non-secular, loading-induced geocenter motion.

• Network shift approach:– Weekly AC solutions theoretically CM-centered.– AC → ITRF translations should reflect geocenter motion.– But unlike SLR, GNSS have so far not proven able to reliably observe

geocenter motion through the network shift approach.– Why?

Page 3: Observing geocenter motion with GNSS

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Example of network shift results

– The translations of the different IGS ACs show various features.– But none properly senses the X & Z components of geocenter motion.

— SLR (smoothed)— GPS (ESA)— GPS (ESA, smoothed)

Annual signal missed

Spurious peaks at

harmonics of 1.04 cpy

Why?

Page 4: Observing geocenter motion with GNSS

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(Multi-) Collinearity

• Consider the linear regression model:y = Ax + v = Σ Aixi + v

– Ai = ∂y / ∂xi = « signature » of xi on the observations

• Collinearity = existence of quasi-dependenciesamong the Ai’s

• Consequences:– Some (linear combinations of) parameters cannot be reliably inferred,– are extremely sensitive to any modeling or observation error,– have large formal errors.

observations parameters residuals

Page 5: Observing geocenter motion with GNSS

• Is the estimation of a particularparameter xi subject tocollinearity issues?– θi = angle between Ai and the hyper-

plane Ki containing all other Aj’s

– VIFi = 1 / sin²θi

– θi = π/2 (VIFi = 1) : xi is uncorrelated with any other parameter.

– θi → 0 (VIFi → ∞) : xi tends to be indistinguishable from the other parameters.

• If yes, why?– The orthogonal projection αi of Ai on Ki corresponds to the linear

combination of the xj’s which is the most correlated with xi. 5

Variance inflation factor (VIF)

Page 6: Observing geocenter motion with GNSS

• Geocenter coordinates are not explicitly estimated parameters.– They are implicitly realized through station coordinates.→ Extend previous notions to such « implicit parameters ».

• There are perfect orientation singularities.→ Extend previous notions so as to handle singularities supplemented

by minimal constraints.

• The whole normal matrix is not available.– Clock parameters are either reduced or annihilated by forming

double-differenced observations.→ Practical collinearity diagnosis (next slide)

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Mathematical difficulties

Page 7: Observing geocenter motion with GNSS

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0)

1)

2)

– Simulate « perfect » observationsx0 → y0

– Introduce a 1 cm error on the Z geocenter coordinate:x1 = x0 + [0, 0, 0.01, …, 0, 0, 0.01, 0, …0]T

– Re-compute observations → y1

– Solve the constrained LSQ problem:

(How can the introduced geocenter error be compensated / absorbed by the other parameters?)

→ x2, y2

error geocenter the keeping whileyyminimize 02

VIFerror remainingerrorintroduced

yy

yy2

02

201

error introducederror absorbed""

yy

yyyy2

01

202

201

coordinate geocenter Z the with correlated most the is which

parametersof ncombinatio linearxx 12

Practical diagnosis

Page 8: Observing geocenter motion with GNSS

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« Signature » of a geocenter shift

• From the satellite point of view:

GPS LAGEOS

δZgc = 1 cm

δXgc = 1 cm

· impact on a particular observation— epoch mean impact

Page 9: Observing geocenter motion with GNSS

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1st issue: satellite clock offsets

• Satellite clocks ↔ constant per epoch and satellite→ The epoch mean geocenter signature is 100% absorbable by

(indistinguishable from) the satellite clock offsets.→ The GNSS geocenter determination can only rely on a 2nd order signature.

• In case of SLR :– The epoch mean signatures of Xgc and Ygc are directly observable.

→ No collinearity issue for Xgc and Ygc (VIF ≈ 1)

– The epoch mean signature of Zgc is absorbable by the satellite osculating elements.→ Slight collinearity issue for Zgc (VIF ≈ 9)

Page 10: Observing geocenter motion with GNSS

2nd order geocenter signature

10

δZgc = 1 cm δXgc = 1 cm

• 2nd issue: collinearity with station parameters– Positions, clock offsets, tropospheric parameters

Page 11: Observing geocenter motion with GNSS

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So what’s left?

• δXgc = 1 cm:

From the point of view of a satellite… …and of a station

• VIF > 2000 for the 3 geocenter coordinates!(More than 99.96% of the introduced signal could be absorbed.)

· impact on an observation, before compensation · impact on an observation, after compensation

Page 12: Observing geocenter motion with GNSS

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Role of the empirical accelerations– The insensitivity of GNSS to geocenter

motion is mostly due to the simultaneous estimation of clock offsets and tropospheric parameters.

– The ECOM empirical accelerations only slightly increase the collinearity of theZ geocenter coordinate.

– This increase is due to the simultaneous estimation of D0, BC and BS:

Page 13: Observing geocenter motion with GNSS

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Conclusions (1/2)

• Current GNSS are barely sensitive to geocenter motion.– The 3 geocenter coordinates are extremely collinear with other GNSS

parameters, especially satellite clock offsets and all station parameters.

– Their VIFs are huge (at the same level as for the terrestrial scale when the satellite z-PCOs are estimated).

– The GNSS geocenter determination can only rely on a tiny 3rd order signal.

– Other parameters not considered here (unfixed ambiguities) probably worsen things even more (cf. GLONASS).

Page 14: Observing geocenter motion with GNSS

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Conclusions (2/2)

• The empirical satellite accelerations do not have a predominant role.– Contradicts Meindl et al. (2013)’s conclusions

• What can be done?– Reduce collinearity issues

(highly stable satellite clocks?)

– Reduce modeling errors(radiation pressure, higher-order ionosphere…)

– Continue to rely on SLR…

Page 15: Observing geocenter motion with GNSS

Thanks for your attention!

For more:

Rebischung P, Altamimi Z, Springer T (2013) A collinearity diagnosis of the GNSS geocenter determination. Journal of Geodesy. DOI: 10.1007/s00190-013-0669-5

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Page 16: Observing geocenter motion with GNSS

Parameter response to δZgc = 1 cm

Network distortion:

→ Explains the significant correlations between origin & degree-1 deformations observed in the IGS AC solutions

ZWDs:(as a function of time, for each station)

And their means:(as a function of latitude)

Station clock offsets:(as a function of time, for each station)

And their means:(as a function of latitude)

Tropo gradients:(as a function of latitude)

N/S gradients

W/E gradients

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Page 17: Observing geocenter motion with GNSS

Zgc collinearity issue in SLR

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• δZgc = 1 cm:

– This slight collinearity issue probably contributes to the lower qualityof the Z component of SLR-derived geocenter motion.

– To be further investigated…

gcgc

gc

2

δZa

siniδe

-ω:0e

δZasinωsini

δe

δZcosωsiniae

e1δM

:0e

· impact on an observation, before compensation · impact on an observation, after compensation— radial orbit difference

– The epoch mean signature of δZgc is compensated by a periodic change of the orbit radius obtained through:

→ VIF ≈ 9.0