An empirical model of long-term thermospheric density change

Predicting the positions of satellites in Low Earth Orbit (LEO) requires a comprehensive understanding of the dynamic nature of the atmosphere. For objects in LEO the most significant orbit perturbation is atmospheric drag, which is a function of the local atmospheric density from a layer in the atmosphere called the thermosphere. For long-term predictions of satellite orbits and ephemerides, any density trend in the thermosphere is a necessary consideration, not only for satellite operators, but also for studies of the future LEO environment in terms of space debris. Numerous studies of long-term thermospheric density change have been performed. Predictions by Roble & Ramesh (2002), along with evidence by Keating (2000), Emmert et al.(2004), Marcos et al. (2005), Qian et al. (2006) and Emmert et al. (2008), strongly suggest the existence of such a phenomenon. Therefore, the objective of the research presented in this thesis is to provide a novel method to evaluate quantitatively thermospheric density change. Satellite drag data is an effective medium through which one can investigate local thermospheric density and changes thereof. There are many ways of determining atmospheric density, but inferring thermospheric density from satellite drag data is a relatively cost-effective way of gathering in-situ measurements. To do this, knowledge about a satellite’s physical properties that are intrinsic to atmospheric drag is required. A study by Saunders et al. (2009) highlighted problems with estimating a satellite’s physical properties directly from data given explicitly by Two-Line Element (TLE) sets. This prompted an investigation into ways to estimate ballistic coefficients: a required satellite parameter associated with drag coefficient and area-to-mass ratio. A novel way of estimating satellite ballistic coefficients was derived and is presented in this thesis. Additionally, novel consideration of atmospheric chemical composition was applied on long-term drag coefficient variability. Using a quantitative estimate of a ballistic coefficient one can propagate numerically a satellite’s orbit and predict the effects of atmospheric drag. Given an initial satellite orbit from TLE data, one approach is to use an orbital propagator to predict the satellite’s state at some time ahead and then to compare that state with TLE data at the same epoch. The difference between the semi-major axes of the initial orbit and that after the orbit propagation is then integrated and can be used to estimate the global average density. The method employed in this study utilises this process. To achieve this, a specially developed, computer-based, numerical orbital propagator was written in the programming language C/C++. The underlying theories and implementation tests for this propagator are presented in this thesis.EThOS - Electronic Theses Online ServiceGBUnited Kingdo