Debiasing of two-line element sets for batch least squares pseudo-orbit determination in MEO and GEO

• Deterministic biases exist in Two-Line Element Sets (TLEs) due to mismodelling of the Lunar perturbation in SGP4. • The bias period is commensurate to the orbital period of the Moon and degrades accuracy of Pseudo-Orbit Determination (P-OD). • Debiasing can be performed by either using long fit windows, of the order of months, or through a simple sinusoidal model. • P-OD with biased TLEs is discouraged as debiasing leads to up to 80% reduction in post-fit position error. The availability of accurate and timely state predictions for objects in near-Earth orbits is becoming increasingly important due to the growing congestion in key orbital regimes. The Two-Line Element Set (TLE) catalogue remains, to this day, one of the few publicly-available, comprehensive sources of near-Earth object ephemerides. At the same time, TLEs are affected by measurement noise and are limited by the low accuracy of the SGP4 theory, introducing significant uncertainty into state predictions. Previous literature has shown that filtering TLEs with batch least squares methods can yield significant improvements in long-term state prediction accuracy. However, this process can be highly sensitive to TLE quality which can vary throughout the year. In this study, it is shown that either extended-duration fit windows of the order of months, or the removal of systematic biases in along-track position prior to state estimation can produce significant reductions in post-fit position errors. Simple models for estimating these systematic biases are shown to be effective without introducing the need for high-complexity Machine Learning (ML) models. Furthermore, by establishing a TLE-based error metric, the need for high accuracy ephemerides is removed when creating these models. For selected satellites in the Medium Earth Orbit (MEO) regime, post-fit position errors are reduced by up to 80%, from approximately 5 km to 1 km; meanwhile, for selected satellites in the Geostationary Earth Orbit (GEO)/Geosynchronous Earth Orbit (GSO) regime, large oscillations in post-fit position error can be suppressed.

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Publication Details

Journal
Advances in Space Research
Published
2025-03-28
DOI
https://doi.org/10.1016/j.asr.2025.03.046
Citations
3
Primary Topic
Space Satellite Systems and Control
Type
article
Field-Weighted Citation Impact
14.98
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article

Debiasing of two-line element sets for batch least squares pseudo-orbit determination in MEO and GEO

Davide Amato, Max I. Hallgarten La Casta
3 citations
Advances in Space Research
Space Satellite Systems and Control
14.98
article

Debiasing of two-line element sets for batch least squares pseudo-orbit determination in MEO and GEO

Davide Amato, Max I. Hallgarten La Casta
article en
3 citations

Abstract

• Deterministic biases exist in Two-Line Element Sets (TLEs) due to mismodelling of the Lunar perturbation in SGP4. • The bias period is commensurate to the orbital period of the Moon and degrades accuracy of Pseudo-Orbit Determination (P-OD). • Debiasing can be performed by either using long fit windows, of the order of months, or through a simple sinusoidal model. • P-OD with biased TLEs is discouraged as debiasing leads to up to 80% reduction in post-fit position error. The availability of accurate and timely state predictions for objects in near-Earth orbits is becoming increasingly important due to the growing congestion in key orbital regimes. The Two-Line Element Set (TLE) catalogue remains, to this day, one of the few publicly-available, comprehensive sources of near-Earth object ephemerides. At the same time, TLEs are affected by measurement noise and are limited by the low accuracy of the SGP4 theory, introducing significant uncertainty into state predictions. Previous literature has shown that filtering TLEs with batch least squares methods can yield significant improvements in long-term state prediction accuracy. However, this process can be highly sensitive to TLE quality which can vary throughout the year. In this study, it is shown that either extended-duration fit windows of the order of months, or the removal of systematic biases in along-track position prior to state estimation can produce significant reductions in post-fit position errors. Simple models for estimating these systematic biases are shown to be effective without introducing the need for high-complexity Machine Learning (ML) models. Furthermore, by establishing a TLE-based error metric, the need for high accuracy ephemerides is removed when creating these models. For selected satellites in the Medium Earth Orbit (MEO) regime, post-fit position errors are reduced by up to 80%, from approximately 5 km to 1 km; meanwhile, for selected satellites in the Geostationary Earth Orbit (GEO)/Geosynchronous Earth Orbit (GSO) regime, large oscillations in post-fit position error can be suppressed.

Advances in Space ResearchVol. 75(10)
Imperial College London (GB)
Openalex Percentile: Top 2%
Space Satellite Systems and Control
14.98
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Debiasing of two-line element sets for batch least squares pseudo-orbit determination in MEO and GEO — Davide Amato, Max I. Hallgarten La Casta · Advances in Space Research (2025) | TGRS Research Map | TGRS