Galileo disposal strategy: stability, chaos and predictability

Abstract

Recent studies have shown that the medium-Earth orbit (MEO) region of the Global Navigation Satellite Systems is permeated by a devious network of lunisolar secular resonances, which can interact to produce chaotic and diffusive motions. The precarious state of the four navigation constellations, perched on the threshold of instability, makes it understandable why all past efforts to define stable graveyard orbits, especially in the case of Galileo, were bound to fail; the region is far too complex to allow of an adoption of the simple geosynchronous disposal strategy. We retrace one such recent attempt, funded by ESA's General Studies Programme in the frame of the GreenOPS initiative, that uses a systematic parametric approach and the straightforward maximumeccentricity method to identify long-term stable regions, suitable for graveyards, as well as large-scale excursions in eccentricity, which can be used for post-mission deorbiting of constellation satellites. We then apply our new results on the stunningly rich dynamical structure of the MEO region toward the analysis of these disposal strategies for Galileo, and discuss the practical implications of resonances and chaos in this regime. We outline how the identification of the hyperbolic and elliptic fixed points of the resonances near Galileo can lead to explicit criteria for defining optimal disposal strategies.

Medium Earth Orbit dynamical survey and its use in passive debris removal

“…Lunisolar resonances are known to overlap near the GNSS region, when mapped in the (a, i) or (e, i) plane (Rosengren et al, 2015;Daquin et al, 2016), a property that adds complexity (chaos) in the dynamics. The long-term effect of resonances in the GNSS region have been studied, using both analytical and numerical methods, on the averaged equations of motion (e.g., see Rosengren et al, 2015;Stefanelli and Metris, 2015;Celletti and Galeş, 2016;Daquin et al, 2016;Gkolias et al, 2016;Rosengren et al, 2017).…”

“…Hence the basic (passive) removal strategy would consist either in (a) assisting eccentricity build-up to reach a reentry solution within a reasonable time, or (b) moving to a long-term stable graveyard orbit. Both strategies would need to take into account the boundaries of the operation zones, the resonant dynamics in the neighborhood, and the need for low-cost maneuvers (Radtke et al, 2015;Alessi et al, 2016;Rosengren et al, 2017;Armellin and San-Juan, 2018). In the eccentricity build-up scenario, usable disposal orbits should have low-to-moderate eccentricities, so to be reachable with low ∆V ; in this paper we set the limit to 300 m/sec.…”

Dynamical cartography of Earth satellite orbits

“…The nonnegligible collision risks posed by these LEO-GEO transiting spacecraft has motivated both theoretical study and practical implementation (Armellin et al, 2015;Colombo et al, 2015;Merz et al, 2015). Even for the, seemingly more simple, inclined, nearly circular orbits of the navigation satellites, no official guidelines exist, and recent analyses have shown that the problem is far too complex to allow of an adoption of the basic geosynchronous graveyard strategy (Rosengren et al, 2015;Daquin et al, 2016;Celletti et al, 2016;Gkolias et al, 2016;Rosengren et al, 2017;Skoulidou et al, 2017) Fig. 1.…”

Drift and Its Mediation in Terrestrial Orbits

“…This scalpel has been used extensively over the past decade across different dynamical problems, ranging from Symplectic Maps studies to Dynamical Astronomy, including Astrodynamical practical problems [38][39][40][41]. The work of C. Froeschlé, M. Guzzo and E. Lega over the last decade provides a good overview of its possibilities and range of applications.…”

“…Very often diameters-like quantities in terrestrial dynamics have been estimated using a more restrictive definition, namely a one-dimensional diameter of a specific observable f (see e.g., [41,46]). This strategy reduces to nothing else than the amplitude estimation, equivalent to the estimation of f = max t f (x) − min t f (x).…”