JuliaCon 2026

Using JuliaC for spacecraft radio interference analysis
2026-08-14 , Room 5

This talk will highlight a JuliaC usecase: developing an Aerospace industry product. Specifically, it will describe the functionality of a SaaS Aerospace product targeting teams involved in space missions, as well as administrative entities. The developed software uses Julia for all simulations, and is compiled to a shared library through JuliaC.jl. The Julia C FFI is used to interface with the main C++ logic, and there's build system (CMake) and CI support.


Spacecraft typically need to transmit and receive information, to/from either other spacecraft, or stations on earth. Reasons why include the ability to transmit scientific data (e.g., captured images), or the ability to investigate on-board sensor measurements and to patch the running software that dictates spacecraft operations while in-orbit. Data transmission usually happens over radio frequencies.

The International Telecommunications Union (ITU) oversees frequency allocation to avoid harmful interference between radio stations: there is a certain bureaucratic procedure to go through to receive the permission to operate at a specific frequency. Identifying potential interference events before they take place is very important. As such, it is typical for administrative entities (e.g., ministries) to inquire about potential interference from the very moment a frequency has been allocated by the ITU. Then, people from the space mission team or organization do back-of-the-envelope calculations to either identify or reject the need for frequency coordination.

This process of evaluating potential interference events is low-accuracy and time-consuming. Low accuracy also means low confidence, which usually leads to the entities being overly conservative in their response (e.g., completely avoiding transmission over a specific country).

The tool is used to identify and evaluate potential radio interference between space and earth stations according to globally enforced regulations. Leveraging Julia for the simulation code allows for high performance, greatly reducing simulation time. This, in turn, enables for high-order features such as running simulation ensembles to identify the least conservative approach to address interference issues, maximizing bandwidth and station coverage.

I've used Julia to make an in-orbit satellite go from spinning too fast to spinning less fast

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