Performance Bounds for Cooperative Localisation in the Starlink Network

C. Turner, R.T. Rajan

Research output: Other contributionProfessional

Abstract

Mega-constellations in Low Earth Orbit have the potential to revolutionise worldwide internet access. The concomitant potential of these mega-constellations to impact space sustainability, however, has prompted concern from space actors as well as provoking concern in the ground-based astronomy community. Increasing the knowledge of the orbital state of satellites in mega-constellations improves space situations awareness, reducing the need for collision avoidance manoeuvres and allowing astronomers to prepare better observational mitigation strategies. In this paper, we create a model of Phase 1 of Starlink, one of the more well-studied megaconstellations, and investigate the potential of cooperative localisation using time-ofarrival measurements from the optical inter-satellite links in the constellation. To this end, we study the performance of any unbiased estimator for localisation, by calculating the instantaneous Crame´r-Rao bound for two situations; one in which inter-satellite measurements and measurements from ground stations were considered, and one in which only relative navigation from inter-satellite measurements were considered. Our results show that localisation determined from a combination of inter-satellite measurements and ground stations can have at best an an average RMSE of approximately 10.15 metres over the majority of a satellite's orbit. Relative localisation using only inter-satellite measurements has a slightly poorer performance with an average RMSE of 10.68 metres. The results show that both anchored and anchorless inter-satellite cooperative localisation are dependent on the constellation's geometry and the characteristics of the inter-satellite links, both of which could inform the use of relative navigation in large satellite constellations in future.
Original languageEnglish
Number of pages27
DOIs
Publication statusPublished - 2022

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