基于AR模型的低轨卫星大气密度建模与预报

Atmosphere Density Modeling and Prediction in Low Earth Orbit Based on AR Model

研究了采用时间序列分析进行低轨卫星大气密度的建模与预报。通过对低轨卫星历史和当前的大气密度进行时间序列建模、频谱分析,可以获得未来数个轨道周期内大气密度的预报模型,并结合GRACE卫星加速度计反演的大气密度数据进行了详细分析。研究结果表明:GRACE卫星一个轨道周期内的密度预报模型是以轨道角速度和时间表示的最高次数为2的傅里叶级数。与三维密度模型相比,这种密度预报模型仅与历史的大气密度有关、所需模型参数少,可为今后在卫星定轨和轨道预报工作中大气密度的建模和预报提供新的思路。

An atmosphere density model and prediction method for LEO satellite was proposed by using time series analysis. The atmosphere density prediction model in next few orbital periods can be derived by time series modeling and spectral analysis of previously and currently measured density values,which is analyzed using the derived atmosphere density from GRACE accelerometer observations. The results show that the atmosphere density prediction model in next orbital period of GRACE can be represented by a Fourier series. Compared with current three-dimensional density model,this atmosphere density prediction model requires fewer coefficients,only concerned with previously density values. The work of this paper has provided new ideas to atmosphere density prediction modeling in satellite orbit determination and forecast.