Optimal location of optical ground stations to serve LEO spacecraft

• Published in: 2017 IEEE Aerospace Conference pp. 1 - 16
• Main Authors: del Portillo, Inigo, Sanchez, Marc, Cameron, Bruce, Crawley, Edward
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-03-2017
• Subjects: Atmospheric modeling; Clouds; Low earth orbit satellites; Orbits; Radio frequency; Stochastic processes
• DOI: 10.1109/AERO.2017.7943631

Free space optical communications (FSO) are envisioned as a disruptive technology for space communications. Among its advantages, FSO will allow higher throughputs (in the order of tenths of Gbps, which represents an improvement of 10 to 100 times with respect to current RF technology), together with significant reductions in size, weight, and power. However, the main drawback of FSO when compared to RF is the reduced link availability due to outages caused by cloud coverage over the receiving ground stations. Site diversity has already been proven to be an effective mitigation technique against cloud outage for geostationary satellites, but its usefulness in the context of low Earth orbit satellites can be challenged by correlated cloud coverage among all visible ground stations. This consideration, along with trade-offs between minimal cloud probability, minimal latency and proximity to supporting infrastructure should all be taken into account when selecting locations for networks of ground stations. This paper presents a model to optimally determine the location of optical ground stations to serve LEO missions, considering the aforementioned trade-offs. First we describe the atmospheric, latency, and infrastructure models used to evaluate the goodness of a network. Second, we statistically characterize the orbits of the customer missions that the ground network will serve. Finally, we present two case studies: The first one selects the best stations among a group of existing assets (stations in the Near Earth Network, other governmental agencies, and commercial facilities from ground segment operators). The second one determines the optimal locations for the ground stations considering an unconstrained scenario in which facilities can be placed at any point on the Earths surface. For each of these scenarios, we report the availability, latency and cost of ground stations of the Pareto-optimal networks.