Thermospheric density uncertainty propagation based on linearized relative orbital dynamics.

Saved in:
Bibliographic Details
Title: Thermospheric density uncertainty propagation based on linearized relative orbital dynamics.
Authors: Krückel, Roman1 (AUTHOR) roman.krueckel@ins.uni-stuttgart.de, Hobiger, Thomas1 (AUTHOR)
Source: Advances in Space Research. May2026, Vol. 77 Issue 9, p9088-9104. 17p.
Subjects: Atmospheric density, Relative motion, Uncertainty (Information theory), Gaussian processes, Earth's orbit, Monte Carlo method
Abstract: • Classical mean anomaly methods overestimate short-term density uncertainty. • Relative orbital dynamics improves short-term uncertainty prediction capability. • An analytical model based on the HCW equations is developed. • Numerical covariance propagation supports correlated Gauss–Markov density errors. • Applicability of model was proven for different orbits and physical parameters. Thermospheric density uncertainty is the dominant source of uncertainty for orbit prediction in Low Earth Orbit (LEO) and Very Low Earth Orbit (VLEO). While analytical uncertainty propagation methods based on mean orbital elements accurately capture long-term secular drift, they fail to represent short-term dynamics, leading to a significant overestimation of along-track uncertainty for prediction horizons below one orbital period. These short-term dynamics are characterized by a zero-crossing of the along-track error caused by the initial differential drag acceleration counteracting the secular drift known as the drag paradox. This limitation is addressed in this paper in the form of an uncertainty propagation model based on linearized relative orbit mechanics using the Hill-Clohessy-Wiltshire (HCW) equations. An analytical solution is derived to characterize the zero-crossing phenomenon and evaluate the effect on the along-track uncertainty. To account for time-varying dynamics and temporally correlated atmospheric density errors, the model is extended using Linear Covariance Propagation with a First-Order Gauss–Markov Process (GMP). Validation with Monte Carlo simulations demonstrates that the numerical HCW model accurately reproduces the empirical uncertainty and the zero-crossing effect that the mean element approaches miss. A sensitivity analysis confirms the model's robustness as well as the general zero-crossing behavior across varying altitudes, correlation times and solar activities while identifying valid propagation timeframes and the limiting effects of orbital eccentricity. [ABSTRACT FROM AUTHOR]
Copyright of Advances in Space Research is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 192967960
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Thermospheric density uncertainty propagation based on linearized relative orbital dynamics.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Krückel%2C+Roman%22">Krückel, Roman</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> roman.krueckel@ins.uni-stuttgart.de</i><br /><searchLink fieldCode="AR" term="%22Hobiger%2C+Thomas%22">Hobiger, Thomas</searchLink><relatesTo>1</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Advances+in+Space+Research%22">Advances in Space Research</searchLink>. May2026, Vol. 77 Issue 9, p9088-9104. 17p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Atmospheric+density%22">Atmospheric density</searchLink><br /><searchLink fieldCode="DE" term="%22Relative+motion%22">Relative motion</searchLink><br /><searchLink fieldCode="DE" term="%22Uncertainty+%28Information+theory%29%22">Uncertainty (Information theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Gaussian+processes%22">Gaussian processes</searchLink><br /><searchLink fieldCode="DE" term="%22Earth's+orbit%22">Earth's orbit</searchLink><br /><searchLink fieldCode="DE" term="%22Monte+Carlo+method%22">Monte Carlo method</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: • Classical mean anomaly methods overestimate short-term density uncertainty. • Relative orbital dynamics improves short-term uncertainty prediction capability. • An analytical model based on the HCW equations is developed. • Numerical covariance propagation supports correlated Gauss–Markov density errors. • Applicability of model was proven for different orbits and physical parameters. Thermospheric density uncertainty is the dominant source of uncertainty for orbit prediction in Low Earth Orbit (LEO) and Very Low Earth Orbit (VLEO). While analytical uncertainty propagation methods based on mean orbital elements accurately capture long-term secular drift, they fail to represent short-term dynamics, leading to a significant overestimation of along-track uncertainty for prediction horizons below one orbital period. These short-term dynamics are characterized by a zero-crossing of the along-track error caused by the initial differential drag acceleration counteracting the secular drift known as the drag paradox. This limitation is addressed in this paper in the form of an uncertainty propagation model based on linearized relative orbit mechanics using the Hill-Clohessy-Wiltshire (HCW) equations. An analytical solution is derived to characterize the zero-crossing phenomenon and evaluate the effect on the along-track uncertainty. To account for time-varying dynamics and temporally correlated atmospheric density errors, the model is extended using Linear Covariance Propagation with a First-Order Gauss–Markov Process (GMP). Validation with Monte Carlo simulations demonstrates that the numerical HCW model accurately reproduces the empirical uncertainty and the zero-crossing effect that the mean element approaches miss. A sensitivity analysis confirms the model's robustness as well as the general zero-crossing behavior across varying altitudes, correlation times and solar activities while identifying valid propagation timeframes and the limiting effects of orbital eccentricity. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Advances in Space Research is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=192967960
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.asr.2026.03.043
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 9088
    Subjects:
      – SubjectFull: Atmospheric density
        Type: general
      – SubjectFull: Relative motion
        Type: general
      – SubjectFull: Uncertainty (Information theory)
        Type: general
      – SubjectFull: Gaussian processes
        Type: general
      – SubjectFull: Earth's orbit
        Type: general
      – SubjectFull: Monte Carlo method
        Type: general
    Titles:
      – TitleFull: Thermospheric density uncertainty propagation based on linearized relative orbital dynamics.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Krückel, Roman
      – PersonEntity:
          Name:
            NameFull: Hobiger, Thomas
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 02731177
          Numbering:
            – Type: volume
              Value: 77
            – Type: issue
              Value: 9
          Titles:
            – TitleFull: Advances in Space Research
              Type: main
ResultId 1