RF Interference Classification and Geolocation

Recorded RF data, especially when captured at a high sample rate requires a lot of bandwidth to downlink to The ground from a satellite constellation. Therefore, it It would be advantageous to process the RF captures on the satellite itself and only downlink interference classification and geolocation data.

Aerospace will provide simulated RF data with representative Global Navigation Satellite System (GNSS) interference signals.

The student team shall develop an algorithm (potentially machine learning) to classify an interference signal –As potential stretch goals: • optimize the algorithm to run on a low- size/weight/power computing platform (e.g., suitable for small satellites) • add jammer pointing direction estimation or geolocation capabilities