Debiasing of Two-Line Element Sets for Batch Least Squares Pseudo-Orbit Determination in MEO and GEO
Max I. Hallgarten La Casta, Davide Amato

TL;DR
This paper improves the accuracy of TLE-based orbit predictions in MEO and GEO by debiasing and extending fit windows, reducing errors significantly without complex models.
Contribution
It introduces simple bias correction models and extended fit windows to enhance TLE-based orbit prediction accuracy in MEO and GEO.
Findings
Post-fit position errors reduced by up to 80% in MEO.
Bias removal suppresses oscillations in GEO predictions.
Extended fit windows improve long-term prediction accuracy.
Abstract
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…
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Taxonomy
TopicsSpace Satellite Systems and Control · Inertial Sensor and Navigation · Satellite Image Processing and Photogrammetry
