Atmospheric density modeling process using data from multiple satellites

Abstract

A moderate resolution model and computer coed to predict atmospheric density from data of atmospheric drag on satellites. Changes in atmospheric density are easily seen by plotting data from TLE sets, but the data is noisy and generally has many gaps in it. This new process presents a way in which data from several different satellites can be scaled to the same level and merged to form a much better model without gaps and solutions where noise values are averaged to reduce their effects. This results in a model that describes the relative changes in the atmospheric density over time. The absolute density is not modeled in this step, however, using satellites with well know drag properties, the model can be calibrated to give estimates of absolute atmospheric density if necessary. Along with the absolute values, the drag coefficients of all the satellites involved can be estimated.

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