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Atmospheric mass density (AMD) plays a vital role in the drag calculation for space objects in low Earth orbit (LEO). Many empirical AMD models have been developed and used for orbit prediction and...

Atmospheric drag, as one of the largest non-gravitational perturbations in low Earth orbit (LEO), can dramatically decay the orbit of LEO satellites with both secular and periodic effects. Hence, it plays a critical role in orbit prediction related products, and research on orbit determination, orbital uncertainty propagation and collision avoidance. Although many empirical thermospheric mass density (TMD) models have been proposed in the past few decades, precise determination of atmospheric drag is still a challenging task. In order to give a comprehensive review of the current empirical TMD models, focusing on their impact on orbital dynamics, this review summarises and investigates the most representative classes of models, including the Jacchia, Mass Spectrometer Incoherent Scatter (MSIS), Jacchia-Bowman (JB), and Drag Temperature Model (DTM). Twelve representative models are selected for further comparison in terms of spatial variations and assessing their ability to capture complex features, e.g., equatorial mass density anomaly (EMA). Further validation is done with accelerometer-derived TMD from LEO satellites. The results show that only DTM2013 can capture the EMA feature and the drag coefficient calculated by physical models used in the TMD estimation may be underestimated. The performance of these models in orbit prediction is comprehensively evaluated under different solar and geomagnetic conditions. JB2008 and DTM2013 outperform the other selected models during low and high solar activity. Standard deviation is found to be less affected by the bias in the accelerometer- and model-derived TMD, than mean value and root-mean-square error. The coupling effect between the TMD and ballistic coefficient, and the potential directions for future efforts in TMD modelling are also discussed.

A new parameter is introduced, termed the density index, which enables the solar activity cycle to be captured in a new analytical atmospheric density model. Consequentially, a new solar activity model is developed that uses a single independent variable per solar cycle to describe the solar activity across that cycle, as indicated by the F10.7 index. These models are combined and applied to a well-known general perturbations method for satellite orbit lifetime analysis, which is first modified using modern mathematical tools to remove simplifications in the derivation. Validation against historical data shows an improvement in orbit lifetime estimates from an average error of 50.44 percent with a standard deviation of 24.96 percent, to an average error of 3.46 percent with a standard deviation of 3.25 percent. Furthermore, the new method with applied atmospheric and solar activity models is found to compare favorably against other general and special perturbations methods, including third party, and commercial software, the most accurate of which was found to have an average error of 6.63 percent and standard deviation of 7.00 percent. A case study, the UKube-1 spacecraft, is presented and it is found that the spacecraft was inserted into an orbit 54km lower than required to comply with best-practice guidelines, and that with 1σ confidence its orbit will decay in June 2028 ± 2 years, and June 2028 ± 4 months if the next solar cycle is an average magnitude cycle.

A general perturbations method for orbit lifetime analysis is extended to include an analytical non-spherically-symmetrical atmospheric density model. This improvement allows the method to be applied with confidence to highly inclined orbits and special cases such as sun-synchronous orbits where the inclusion of the effects of atmospheric oblateness and the diurnal bulge will be particularly significant. These improvements can be applied to any general perturbations model for lifetime analysis. Using a case study of a sun-synchronous satellite a comparison is drawn between the original and improved methods, showing that by capturing the effects of a non-spherically-symmetrical atmosphere the orbit lifetime predicted could be up to 7% longer or 10% shorter than when using the spherically-symmetrical model. Also notable is the difference between the orbit lifetime predictions made using the spherically-symmetrical model derived from different data sets; for the case study this was approximately a third of the orbit lifetime.