| Citation: | CHENG Xuan, XIAO Cunying, YANG Junfeng, et al. A modeling method and its application of global atmospheric density in near space[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(12): 2227-2235. doi: 10.13700/j.bh.1001-5965.2019.0614(in Chinese)
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Based on the 20-100 km atmospheric density data observed by TIMED/SABER satellite from year 2002 to 2018, the global grid data of monthly average and standard deviation are calculated statistically. Based on the grid data, the characteristics of atmospheric density variation are analyzed. The relative errors of USSA76 are calculated and the distribution characteristics of relative errors of USSA76 are analyzed. In addition, driven by the grid data, the atmospheric density is characterized as the sum of the monthly average and the large-scale disturbances and small-scale disturbances. The large-scale perturbations and small-scale perturbations are characterized by cosine functions and first-order autoregressive models, respectively. And a global near-space atmospheric density model is initially established. By comparing the simulated values of the model with the observed values of the lidar, the results show that the model values have a good agreement with the observed values, which verifies that the modeling method is feasible. Finally, Monte Carlo method can be used to reproduce all possible states of atmospheric density on a given trajectory.
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