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Sensitivity of Orbit Predictions to Density Variability

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Where should modeling efforts focus to improve orbit ... Magnitude of density. variations. Phase errors (errors in timing) Significant Prediction Errors ... – PowerPoint PPT presentation

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Title: Sensitivity of Orbit Predictions to Density Variability


1
Sensitivity of Orbit Predictions to Density
Variability
  • Rodney L. Anderson
  • George H. Born
  • Jeffrey M. Forbes

2
Where should modeling efforts focus to improve
orbit prediction?
  • Horizontal density scales
  • Type (shape) of density
  • variations
  • Magnitude of density
  • variations
  • Phase errors (errors in timing)

Significant Prediction Errors (over 24 hours)
3
Method
  • Integrate two trajectories from
  • same I.C.s in 2-Body Problem
  • One with Truth
  • density profile
  • One with alternate
  • density profile
  • Compare position (RIC) diff. after ?t
  • All results are for the CHAMP S/C

4
Prediction Differences using CHAMP Model Data
(2003)
Total Difference
In-track Difference
5
Isolate Effect of Different Horizontal Density
Scales
  • Determine component of orbit prediction model
    error caused by different horizontal density
    scales
  • Determine error introduced by missing a single
    wavelength (scale)
  • Integrate one trajectory with nominal density
  • Integrate one trajectory with density
    perturbation function (25 amplitude)
  • Does the type of function matter?
  • Which scales are most important?

6
Sine Wave (1 cycle)
Position Difference
Density over Time
7
Functions Give Similar Results
(1 Cycle Cases)
Diff.max ? 1.3 m
Diff.max ? 1.4 m
Diff.max ? 1.55 m
8
One, Two Three Day Integration Times
Diff.max ? 3 m
Diff.max ? 6 m
Diff.max ? 9 m
In-track Differences
24 hours
48 hours
72 hours
  • Orbit differences with 10,000 km wavelength
    increase by about 3 m per day (CHAMP S/C)

9
Predictions with Measured vs. Smoothed CHAMP Data
  • What happens if multiple wavelengths are ignored?
  • Use smoothing or averaging over different time
    intervals
  • Raw data
  • 6 minute averaging
  • 30 minute averaging
  • Reduces power of shorter wavelengths

10
Smoothed Data (30 min. Interval)
(Day 324 of 2003)
11
Comparison over 2003(24 hour, 6 minute case)
  • Differences are primarily in the in-track
    direction
  • Mean 0.63 m
  • Max. 10.7 m
  • Min. 0.019 m

12
Comparison over 2003(24 hour, 30 minute case)
  • Mean 6.21 m
  • Max. 56.21 m
  • Min. 0.24 m

13
Histogram 30 minute average
2003
2007
14
Conclusions
  • Single wavelength perturbations can give meter
    level errors
  • Neglecting density scales below
  • 1000 km gives meter level errors (for CHAMP)
  • 8000 km gives errors on the order of 10s of
    meters (for CHAMP)
  • Errors small but significant enough to take into
    account in models

15
Current Status
  • Examining contribution of different components to
    error
  • Additional altitudes
  • Eccentric orbits
  • Perturbations that die off
  • Different density altitudes
  • In-phase and out-of-phase perturbations
  • Time delay (phase) issues
  • Implementing density models in GIPSY-OASIS
  • Including additional satellites
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