A methodology for using optimal MSIS parameters retrieved from SSULI data to compute satellite drag on LEO objects

A key application to be derived from Space Weather research will be to forecast atmospheric drag on low Earth orbit (LEO) satellites with significantly better accuracy than is attainable today. The recently launched STP P91-1 ARGOS mission will serve as a testbed for the use of future operational ultraviolet remote-sensing data to achieve such an improvement. This paper describes the associated methodology, which uses discrete inverse theory in conjunction with the data to derive correction factors in near real time for the MSISE-90 empirical thermospheric model. To simulate the application of this technique to orbit prediction, we use the Jacchia-71 operational model to generate an evolving “ground truth” upper atmospheric state over a 48 h time period. This permits a state-of-the-art Satellite Tool Kit orbit propagator to synthesize a corresponding “ground truth” orbit on a standard LEO test object at 350 km altitude. Our tests show that, for orbit prediction, the “data-enhanced” MSIS density specification can provide significant improvement over the uncorrected MSIS specification. However, for orbit prediction, the results are sensitive to the strategy selected for applying the correction factors. We contrast our results for orbit prediction with those of Marcos et al. (1998. Astrodynamics. Vol. 97(1). AAS, San Diego, pp. 501–513) for precision orbit determination. An important result in the context of Space Weather is that the Jacchia and MSIS models can show significant point-to-point disagreement, which has major implications for operational specification of thermospheric drag.