Valuation of On-Orbit Servicing in Proliferated Low-Earth Orbit Constellations

Abstract

On-orbit servicing (OOS) presents new opportunities for refueling, inspection, repair, maintenance, and upgrade of spacecraft (s/c). OOS is a significant area of need for future space growth, enabled by the maturation of technology and the economic prospects. This congestion is leading s/c operators to explore how they can leverage OOS. OOS missions for s/c in geostationary orbit (GEO) are currently underway. This is being driven by the closure of the business case for refueling long lived monolithic chemically propelled GEO assets. However, there are currently no plans for OOS of low-earth orbit (LEO) s/c, aside from technology demonstrations, because of their shorter design life and lower cost. It will become particularly important to enable the servicing of LEO s/c as the industry shifts its focus towards LEO. Designing OOS systems for LEO constellations differs from that of GEO based systems, this difference is attributed to LEO's proliferation of satellites, environmental effects (J2 nodal precession, drag), and different constellation patterns. Satellite constellations in LEO are becoming more distributed due to increased access, distributed risk, flexibility, and cost. OOS of s/c may enable the reduction of requirements on subsystems such as safety and the need for redundancy. These requirement reductions will enable lower risks, lower costs, and increased system resilience. This paper analyzes the benefits of OOS in proliferated LEO constellations. Several OOS system architectures are modeled; in each system architecture the model will vary qualities such as number of servicers, altitudes, and orbital maneuvers. The objective of the model will be to optimize for cost, time, and utility to generate a tradespace for an OOS system architecture.

On-Orbit Servicing System Architectures for Proliferated Low-Earth-Orbit Constellations

“…This system was originally proposed by Northrop Grumman for GEO applications [118]. Additional research on OOS depot methods have been considered and are outside the scope of this paper [6,119,120]. Pods present the most beneficial CONOP to the general solution of an OOS system architecture.…”

Global Optimization via Optimal Decision Trees

“…We test our method on the previously-unsolved optimization problem of satellite on-orbit servicing (OOS) scheduling. Satellite OOS is a future technology that seeks to improve the lifetime of existing and next-generation satellites by allowing autonomous servicer spacecraft to perform repairs or refuels in orbit [Luu and Hastings (2020)]. OOS is a difficult scheduling problem that acts on a highly nonlinear dynamical system.…”

“…In addition, due to the 11 orders of magnitude difference in the ranges of decision variables, it is numerically challenging. Before this paper, it was addressed only via enumeration [Luu and Hastings (2020)]. Please refer to Appendix A.4 for more details on the full list of constraints; a succinct summary of the problem follows.…”

“…We thank Michael Luu for his help in the formulation of the satellite OOS problem in Section 6.2, based on his previous work [Luu and Hastings (2020)].…”

Low-Power Laser Sailing for Fast-Transit Space Flight

“…Massive orbital constellations providing global services (e.g., for Earth observations and Internet) are driving the economic growth . At the same time, rapid proliferation of orbital use faces emerging challenges, including on-orbit servicing of satellites on demand , and collision avoidance, , among others. Yet, at present there are no efficient ways to change a spacecraft orbit after launch, such as performing orbital plane or altitude change maneuvers. , In particular, current chemical and electrical rocket engines require either an exorbitant amount of fuel or many months of flight time to perform desired orbital maneuvers. , A fast and responsive orbital transfer system has yet to be developed.…”