Ionospheric models are applied for computing the Total Electron Content (TEC) in ionosphere to reduce its effects on the Global Navigation Satellite System (GNSS)-based Standard Point Positioning (SPP) applications. However, the accuracy of these models is limited due to the simplified model structures and their dependency on the calibration period. In this study, we present a sequential Calibration approach based on the Ensemble Kalman Filter (C-EnKF) to improve TEC estimations. The advantage of C-EnKF, over the frequently implemented state-of-the-art, is that a short period of GNSS network measurements is needed to calibrate model parameters. To demonstrate the results, the International Reference Ionosphere (IRI)-2016 model is used as reference and the Vertical TEC (VTEC) estimates from 53 IGS (the International GNSS Service) stations in Europe are applied as observation. The C-EnKF is applied to calibrate four selected model parameters (i.e., \(IG_{12}\), URSI(771), URSI(1327) and URSI(1752) related to the ionospheric activity as well as height and density peak-modelling in the F2 layer), which are identified by performing a sensitivity analysis. The calibrated model, called ‘C-EnKF-IRI’, is localized within Europe and can be used for near-real time TEC estimations and forecasting of the next day (at least). Validation against the dual frequency GNSS measurements of three IGS stations indicates that during September 2017, the accuracy of forecasting VTECs is improved up to 64.87% compared to IRI-2016. The electron density (Ne) profiles of C-EnKF-IRI are validated against those of COSMIC products, which indicates \(\sim \)38.1% improvement during days with low (\(Kp=3\)) and high (\(Kp=8\)) geomagnetic activity. Applying the forecasts of VTECs in SPP experiments shows similar performance as the 11-days delayed IONEX data, i.e., 51%, 52% and 79%, improvements in estimating ionospheric contributions compared to the usage of the original IRI-2016, Klobuchar and NeQuick-G models, respectively. The TEC forecasts of C-EnKF-IRI are found to be of the same quality of the IONEX final TEC products in SPP applications.

电离层模型用于计算电离层中的总电子含量 (TEC)，以减少其对基于全球导航卫星系统 (GNSS) 的标准点定位 (SPP) 应用的影响。然而，由于简化的模型结构及其对校准周期的依赖性，这些模型的准确性受到限制。在这项研究中，我们提出了一种基于集成卡尔曼滤波器 (C-EnKF) 的顺序校准方法来改进 TEC 估计。C-EnKF 与经常实施的最新技术相比的优势在于，需要短周期的 GNSS 网络测量来校准模型参数。为了证明结果，国际参考电离层 (IRI)-2016 模型用作参考，欧洲 53 个 IGS（国际 GNSS 服务）站的垂直 TEC (VTEC) 估计值用作观测。C-EnKF 用于校准四个选定的模型参数（即，\(IG_{12}\) , URSI (771), URSI (1327) 和URSI (1752) 与电离层活动以及 F2 层中的高度和密度峰值建模有关），通过执​​行灵敏度识别分析。校准后的模型称为“C-EnKF-IRI”，位于欧洲，可用于近乎实时的 TEC 估计和第二天（至少）的预测。对三个 IGS 站的双频 GNSS 测量结果的验证表明，在 2017 年 9 月期间，与 IRI-2016 相比，预测 VTEC 的准确度提高了 64.87%。C-EnKF-IRI的电子密度 ( Ne ) 分布已与 COSMIC 产品的电子密度 (Ne) 分布对比，这表明\(\sim \)在低 ( \(Kp=3\) ) 和高 ( \(Kp=8\) ) 地磁活动的日子里改善了 38.1%。在 SPP 实验中应用 VTEC 的预测显示出与延迟 11 天的 IONEX 数据相似的性能，即 51%、52% 和 79%，与使用原始 IRI-2016、Klobuchar 和 NeQuick 相比，在估计电离层贡献方面有所改进-G 模型，分别。发现 C-EnKF-IRI 的 TEC 预测与 SPP 应用中的 IONEX 最终 TEC 产品具有相同的质量。