Orbital Debris Tracking Algorithms: TLE, UKF, and EKF Comparison - NextGenBeing Orbital Debris Tracking Algorithms: TLE, UKF, and EKF Comparison - NextGenBeing
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Evaluating Orbital Debris Tracking Algorithms: A Comparative Study of TLE, UKF, and EKF with Orekit 11.0 and Python 3.12

Learn how to improve orbital debris tracking using Orekit 11.0 and Python 3.12. Compare TLE, UKF, and EKF algorithms for accuracy and efficiency.

Data Science Premium Content 3 min read
NextGenBeing Founder

NextGenBeing Founder

Dec 23, 2025 • 11 views
Evaluating Orbital Debris Tracking Algorithms: A Comparative Study of TLE, UKF, and EKF with Orekit 11.0 and Python 3.12
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Introduction to Orbital Debris Tracking

Last quarter, our team encountered significant challenges while tracking orbital debris using traditional methods. The increasing number of satellites and space junk in Earth's orbit necessitates the development of more accurate and efficient tracking algorithms. In this article, I'll share our experience comparing Three-Line Element (TLE), Unscented Kalman Filter (UKF), and Extended Kalman Filter (EKF) algorithms using Orekit 11.0 and Python 3.12.

The Problem with Traditional Methods

Most developers miss the critical step of accounting for non-gravitational forces when using TLE for orbital debris tracking. This oversight can lead to significant errors in position and velocity calculations. To address this, we explored the use of UKF and EKF, which can handle non-linear systems and non-Gaussian noise.

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Tags: space satellites tracking algorithms

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