  This paper discusses the predictive capability of Dynamic Mode Decomposition
(DMD) in the context of orbital mechanics. The focus is specifically on the
Hankel variant of DMD which uses a stacked set of time-delayed observations for
system identification and subsequent prediction. A theory on the minimum number
of time delays required for accurate reconstruction of periodic trajectories of
nonlinear systems is presented and corroborated using experimental analysis. In
addition, the window size for training and prediction regions, respectively, is
presented. The need for a meticulous approach while using DMD is emphasized by
drawing comparisons between its performance on two candidate satellites, the
ISS and MOLNIYA-3-50.
