"Calibration of atmospheric density model using two-line element data" by Yuan Ren and Jinjun Shan

Article Title

Calibration of atmospheric density model using two-line element data

Authors

Yuan Ren, Department of Earth and Space Science and Engineering, York University, Toronto, M3J 1P3, Canada
Jinjun Shan, Department of Earth and Space Science and Engineering, York University, Toronto, M3J 1P3, Canada

Keywords

atmospheric density model, two-line element (TLE)

Abstract

For satellites in orbits, most perturbations can be well modeled; however the inaccuracy ofthe atmospheric density model remains the biggest error source in orbit determination andprediction. The commonly used empirical atmospheric density models, such as Jacchia,NRLMSISE, DTM, and Russian GOST, still have a relative error of about 10%–30%.Because of the uncertainty in the atmospheric density distribution, high accuracy estimationof the atmospheric density cannot be achieved using a deterministic model. A better wayto improve the accuracy is to calibrate the model with updated measurements. Two-line element (TLE) sets provide accessible orbital data, which can be used in the modelcalibration. In this paper, an algorithm for calibrating the atmospheric density model isdeveloped. First, the density distribution of the atmosphere is represented by a power seriesexpansion whose coefficients are denoted by the spherical harmonic expansions. Then, theuseful historical TLE data are selected. The ballistic coefficients of the objects are estimatedusing the BSTAR data in TLEs, and the parameterized model is calibrated by solving anonlinear least squares problem. Simulation results show that the prediction error is reducedusing the proposed calibration algorithm.