Encrypted collision avoidance maneuver via variational optimization

Abstract

We propose an encrypted collision avoidance maneuver (CAM) design protocol using homomorphic encryption (HE) that enables operators to outsource CAM design to an untrusted server without revealing their private covariance. To this end, we reformulate the constrained CAM optimization as a sampling based estimation problem via a variational approach, so that the private covariance dependent terms can be efficiently evaluated under HE. The protocol requires only a single round of communication, and experiments on six real-world conjunction data messages demonstrate improved feasibility and reduced fuel consumption compared with CAMs designed using public covariance.