Very Low Earth Orbit (VLEO) is an increasingly accessible regime of space with payoffs in improved payload performance. However, the denser atmosphere is a persistent challenge as it induces aerodynamic perturbations. Accurate modelling of aerodynamic perturbations is thus crucial to optimize the design of VLEO system lifetime, safety margins and CONOPs development. Modelling tools suitable for quantifying the interactions of the VLEO environment on satellite surfaces have been developed [1] [2]. However, significant residual modelling errors remain which are typically accommodated via conservative engineering margins, thus driving up VLEO systems’ SWaP-C. The inability to characterise these tools stems chiefly from the scarcity of data from satellites in VLEO and that some model parameters, such as gas-surface interaction coefficients, cannot be calibrated from the ground. Further, VLEO aerodynamic studies to-date depend on bespoke sensors such as mass spectrometers and highly sensitive force sensors [3]. In such cases, VLEO experiments have been designed for during the design phase. However, given the relative scarcity of VLEO satellites to-date with such sensors, how could one make use of a satellite in VLEO with only a standard Attitude and Orbit Control Systems (AOCS) sensor and actuator suite to characterise a rarefied aerodynamics model?
 
This work details the characterisation of the accuracy of a rarefied aerodynamics workflow that utilises TPMC against in-orbit data measured by a satellite in VLEO. The main contributions of this work include 1) the calibration of model parameters that cannot be calibrated on the ground, 2) identifying relevant phenomena that a satellite with no bespoke sensors can measure, 3) processing of in-orbit measurements into suitable information for model characterisation and 4) quantifying sources of noise and expected levels of uncertainty that bound the experiment design’s trade space. Developing upon existing VLEO studies, the aerodynamic states at different attitudes were studied. This additional data expands the characterisation of the aerodynamics workflow model to encompass the varying operating attitudes expected in VLEO satellites.
 
The final paper will provide a detailed description of the rarefied aerodynamics workflow-under-test. It will then present a kinematic model based on the measurements that are possible by the satellite’s sensors, incorporating the aerodynamic effects and other perturbations. The design of experiments and finally the processing steps will be described. The characterised accuracy of this aerodynamics workflow-under-test will be shared. A trade-off between approaches utilising bespoke sensors against approaches utilising only a standard AOCS sensor suite will be discussed.

The insights from this characterisation effort have provided increased confidence in this aerodynamics workflow and establishes uncertainty margins driven by real-world measurements. This allows the right-sizing of engineering safeguards of subsystems that are tasked to deal with aerodynamic effects, such as the propulsion system and attitude control actuators.
 
This research outcome provides the following benefits: 1) enable VLEO mission owners to characterise the accuracy of their aerodynamics workflow with a non-intrusive method utilising only standard sensors and a quantifiable trade-off in measurement accuracy and 2) safe optimisation of system SWaP-C through right-sized buffers.


References
[1] S. S. Ramesh, B. Elhadidi, B. C. Khoo and W. L. Chan, “Aerodynamic force and moment computations for very low Earth orbit satellites using a TPMC model,” Acta Astronautica, vol. 228, pp. 88-100, 2025.
[2] J. D. Pedro, T. E. Schwartzentruber, A. Hubin, T. E. Magin and T. K. Minton, “Modeling Hyperthermal O?Atom Scattering Dynamics on Satellite Materials,” The Journal of Physical Chemistry, vol. 129, pp. 12486-12501, 2025.
[3] T. Visser, E. N. Doornbos, C. C. d. Visser, P. N. Visser and B. Fritsche, “Torque model verification for the GOCE satellite,” Advances in Space Research, vol. 62, pp. 1114-1136, 2018.