Atmospheric density modeling process using data from...

Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Earth science

Reexamination Certificate

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Reexamination Certificate

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06477468

ABSTRACT:

BACKGROUND OF THE INVENTION
The present invention relates generally to systems which calculate the effects of the atmosphere n the transmission of radio and optical beams, and more specifically to a new process to model the atmospheric density variations. Typically atmospheric densities are estimated using models that generate predictions based on historical data, or use measurements of indirect values such as solar flux and geomagnetic measurements as input to a model to get values for high altitude atmospheric density. These indirect values are used in lieu of direct measurements of the upper atmosphere. Examples of computer models of the atmosphere are shown in the following U.S. Patens, the disclosures of which are incorporated herein by reference:
U.S. Pat. No. 5,315,513, May 24, 1994, System for modeling moderate resolution atmospheric propagation, Abreu, Leonard W.
U.S. Pat. No. 5,281,815, Jan. 25, 1994, Method of determining the humidity and temperature of atmospheric air, Even-Tov, Ori, and
U.S. Pat. No. 5,075,856, Dec. 24, 1991, System for modeling low resolution atmospheric propagation, Kneizys, Francis X.
SUMMARY OF THE INVENTION
Typically atmospheric densities are estimated using models that generate predictions based on historical data, or use measurements of indirect values such as solar parameters as input to a model to get values for high altitude atmospheric density. This new process uses readily available estimates of drag from satellites' orbital elements to form a model of the atmospheric density changes. The source of the measurements used in the development of this process was from NORAD “Two Line Element (TLE)” sets, but the process is not limited to data from this source.
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 known 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.
This is a potentially better model of the atmospheric density than other models, because it is a direct observation of the atmospheric density's effects instead of estimating the density based on less direct measurements.
It is an object of this invention to provide:
1) improved estimate of orbital parameters (coefficient of drag) for satellites
2) more accurate prediction of satellite positions in the future
3) better understanding of the atmospheric changes over time
4) basis for comparing solar interaction with the atmosphere
5) enhanced ability to predict satellite lifetimes
These and many other objects and advantages of the present invention will be readily apparent to one skilled in the pertinent art from the following detailed description of preferred embodiment of the invention and the related drawings.


REFERENCES:
Sehnal, L., et al., “MIMOSA —a satellite measuring orbital and attitudinal accelerations caused by non-gravitational forces”, Advances in Space Research, vol. 23, No. 4, p. 705-714, Feb. 1999.*
Berger, Jaeck, “Statistical model of global density between 180 and 500 km (deduced from satellite drag data)”, Annales de Geophysique, vol. 29, Oct.-Dec. 1973, p. 547-552.

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