Gravity Gradient Tensor Algorithm for Autonomous Satellite Navigation
J.R. Millan Fernandez (TU Delft - Aerospace Engineering)
João Encanacao de – Mentor (TU Delft - Astrodynamics & Space Missions)
E. Schrama – Graduation committee member (TU Delft - Astrodynamics & Space Missions)
C Siemes – Graduation committee member (TU Delft - Astrodynamics & Space Missions)
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Abstract
This thesis investigates autonomous satellite navigation using gravity gradiometry as an alternative to GNSS. While GNSS depends on external signals, gravity gradiometry allows a satellite to determine its orbit using only on-board measurements and gravity field models. A least squares orbit determination algorithm is developed in Rust, and tested with both uncorrected and corrected versions. The corrected version accounts for calibration parameters such as bias, while the uncorrected does not.
Analyses show that an accurate convergence depends on initial position deviations, orbital altitude, degree and order, calibration parameters and dampening factor. Validation with ESA’s GOCE mission data demonstrates average position errors of 0.688%, primarily due to measurement errors. Applying the algorithm to simulated lunar orbit data yields errors of 0.0000981658%, a significant improvement under more ideal conditions.
The study concludes that gravity gradiometry offers a viable path toward autonomous navigation, with future work needed on calibration refinements and broader orbital testing.