Calibration of Atmospheric Density Model Using Orbital Data of Multiple Satellites

Abstract

In orbit dynamics, most perturbations are well modeled, while the inaccuracy of the atmospheric density model turns into the biggest error source in orbit prediction and determination. The commonly used empirical atmospheric density models, such as, Jacchia, MSIS, DTM and Russian GOST, still have a relative error about 10% − 30%. Because of the uncertainty of the density distribution of atmosphere, estimating the atmospheric density by a deterministic model cannot achieve high accuracy. The better way to improve the model precision is calibrating the model with updated measurements. Two-line element set is accessible orbital data of satellite, which can be used in the model calibration. In this paper, an algorithm for calibrating atmospheric density model is developed. First, the density distribution of atmosphere is represented by a power series expansion whose coefficients are denoted by spherical harmonic expansions. Then, the expansion coefficients and the ballistic coefficients of the satellites are identified simultanteneously by solving a nonlinear least squares problem. The simulation results show that the relative error of the atmospheric density is less than 3%, and the relative error of the ballistic coefficient is less than 0.3% after calibration.