I Can Hear You Coming: RF Sensing for Uncooperative Satellite Evasion

Uncooperative satellite engagements with nation-state actors prompts the need for enhanced maneuverability and agility on-orbit. However, robust, autonomous and rapid adversary avoidance capabilities for the space environment is seldom studied. Further, the capability constrained nature of many space vehicles does not afford robust space situational awareness capabilities that can inform maneuvers. We present a "Cat & Mouse" system for training optimal adversary avoidance algorithms using Reinforcement Learning (RL). We propose the novel approach of utilizing intercepted radio frequency communication and dynamic spacecraft state as multi-modal input that could inform paths for a mouse to outmaneuver the cat satellite. Given the current ubiquitous use of RF communications, our proposed system can be applicable to a diverse array of satellites. In addition to providing a comprehensive framework for an RL architecture capable of training performant and adaptive adversary avoidance policies, we also explore several optimization based methods for adversarial avoidance on real-world data obtained from the Space Surveillance Network (SSN) to analyze the benefits and limitations of different avoidance methods.