New data assimilation techniques have improved time-dependent estimates of the neutral atmospheric density, making it possible to better estimate the drag perturbation on low-Earth-orbiting satellites. This study looks at the potential for using satellite remote sensing from space as an effective density observation source in a data assimilation system. Changes in the neutral density can occur on a minute-to-minute basis, particularly during geomagnetic storms. Although coverage from only a few (two) satellites may be limited, remote sensing provides observations with a high temporal and spatial resolution. To quantify the effectiveness of the observing platform, a simulated “truth” neutral atmosphere is created using a physical model. This “truth” neutral atmosphere is sampled according to the mechanics of the remote sensing platform, and the results are statistically evaluated. With the resolution afforded by remote sensing, results show that two remote sensing satellites provide a stable solution of degree 4 (5 × 5) every ten minutes. Although coverage from two remote sensing satellites is limited, the coverage is sufficient to provide a pattern correlation coefficient consistently higher than 0.92.

中文翻译：

---

数据同化系统中中性大气密度估计的遥感潜力

新的数据同化技术改善了对中性大气密度的时变估计，从而可以更好地估计低地球轨道卫星的阻力扰动。这项研究着眼于利用来自太空的卫星遥感作为数据同化系统中有效的密度观测源的潜力。中性密度的变化可能每分钟发生一次，尤其是在地磁风暴期间。尽管仅少数（两颗）卫星的覆盖范围可能会受到限制，但遥感技术可提供具有高时空分辨率的观测结果。为了量化观测平台的有效性，使用物理模型创建了一个模拟的“真相”中性大气。这种“真实的”中性气氛是根据遥感平台的力学原理进行采样的，并对结果进行统计评估。利用遥感所提供的分辨率，结果表明，两颗遥感卫星每十分钟提供4级（5×5）的稳定解决方案。尽管来自两个遥感卫星的覆盖范围是有限的，但是该覆盖范围足以提供始终高于0.92的模式相关系数。