The analysis of assumptions' error sources on assimilating ground-based/spaceborne ionospheric observations
The analysis of assumptions' error sources on assimilating ground-based/spaceborne ionospheric observations
复制标题
同化地基/星载电离层观测假设误差源分析
DOI：
10.1016/j.jastp.2020.105354
复制
发表时间：
2020
影响因子：
1.9
通讯作者：
Hong Zhenjie
中科院分区：
文献类型：
--
作者：
Fu Naifeng;Guo Peng;Chen Yanling;Wu Mengjie;Huang Yong;Hu Xiaogong;Hong Zhenjie
本文模拟了地基和星载系统的GNSS电离层观测，并通过卡尔曼滤波器算法重建了全局3D电离层密度场。分析了电离层数据同化中的各种误差和影响，提出了相应的改进方法，并通过仿真分析从以下两个方面进行了验证： 1．从倾斜总电子含量（TEC）统计来看：（a）高度在800~20000 km之间的炮弹影响为20~30%，可通过两步同化方法降低； (b) 电离层时间变化的影响可达~10%，经本文提出的修正后，影响降至~5%； (c) 电离层网格表示的影响为 ̃2.5%，通过截距中点双线性插值方法将其降低至 0.9%。上述三种错误被称为假设错误，因为它们总是被理论假设所忽略或推导出来。 2．电子密度重构结果表明，假设误差修正算法优于原始算法，证实了假设误差修正算法的有效性。同时还表明，由于不存在电离层对称假设，卡尔曼滤波同化算法优于Abel-Retrieved方法，特别是在电离层F2区域。
In this paper, GNSS ionospheric observations from ground-based and spaceborne systems were simulated, and the global 3D ionospheric density field was reconstructed by Kalman-Filter algorithm. Various errors and influences in the assimilation of the ionospheric data were analyzed, and corresponding improvement methods were proposed, which were verified from the following two aspects based on simulation analysis:1. From the statistics of slant total electron content(TEC): (a) the influence of the shell with altitude between 800 km and 20000 km was 20̃30%, and could be reduced by the two-step assimilation method; (b) the influence of ionospheric time variations could reach ̃10%, and was reduced to ̃5% by the correction proposed in this paper; (c) the influence of the ionospheric grid representation was ̃2.5%, and was reduced to 0.9% by the method of the bilinear interpolation at intercept midpoint. The three errors mentioned above are called assumptions’ error, for they always be ignored or deduced by theoretical assumptions.2. The results of electron density reconstruction showed algorithm with assumptions errors corrections was better than origin one, which confirmed the effectiveness of the correction algorithms to the assumptions errors. And it was also showed that the Kalman filter assimilation algorithm was better than the Abel-Retrieved method, especially in ionospheric F2 region, for there is no ionospheric symmetric assumption.