An Overview of Autonomous Optical Navigation for Deep-Space CubeSats

A new era of space exploitation is fast approaching. CubeSats have performed a revolution in the way satellites are deployed in interplanetary missions. The exploitation of standardized dimensions and Commercial-Off-The-Shelf components has boosted their utilization by reducing mission costs and development time. The cutting down on the space entry-price grants the democratization of interplanetary exploration. Yet, the flourishing growth of users in space will saturate the ground networks, hindering the traditional navigation through ground-based radiometric tracking. Miniaturized probes that can operate in complete autonomy from the ground represent the solution of this issue. From navigation perspective, a celestial triangulation algorithm fed by optical observations of planets can be exploited to retrieve the probe state. In this work, an autonomous optical navigation algorithm for interplanetary nano-spacecraft applications is developed. In particular, an Extended Kalman Filter featuring line-of-sight acquisitions of planets is adopted as state estimator. The solution accuracy is improved by correcting the planetary light-time and aberration effects and by exploiting the optimal beacons selection strategy. Moreover, an in-depth analysis concerning the numerical precision of the estimator is carried out. Finally, the navigation algorithm is tested on a platform comparable to a CubeSat computer to verify its sustainability and performances. The present work is framed within the EXTREMA project, awarded an ERC Consolidator Grant in 2019.