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

A key application to be derived fi om Space Weather research will be to for ecast atmospheric drag on low Earth orbit (LEO) satellites with significant ly better accuracy than is attainable today. The recently launched STE P91- 1 ARGOS mission will serve as a testbed For the use of future operational u ltraviolet remote-sensing data to achieve such an improvement. This paper d escribes the. associated methodology, which uses discrete inverse theory in conjunction with the data to derive correction factors in near real time f or the MSISE-90 empirical thermospheric model. To simulate the application of this technique to orbit prediction, we use the Jacchia-71 operational mo del to generate an evolving "ground truth" upper atmospheric state over a 4 8 h time period. This permits a state-of-the-art Satellite Tool Kit orbit p ropagator to synthesize a corresponding "ground truth" orbit un a standard LEO test object at 350 km altitude. Our tests show that, for orbit predicti on, thr "data-enhanced" MSIS density specification can provide significant improvement over the uncorrected MSIS specification. However, for orbit pre diction, the results are sensitive to the strategy selected for applying th e correction factors. We contrast our results for orbit prediction with tho se of Marcos et at. (1998. Astrodynamics. Vol. 97(1). AAS, San Diego, pp. 5 01-513) for precision orbit determination, An important result in the conte xt of Space Weather is that the Jacchia and MSIS models can show significan t point-to-point disagreement, which has major implications for operational specification of thermospheric drag. published by Elsevier Science Ltd.