电离层是空间天气和日地空间环境的重要组成部分，不仅在跨电离层无线电传播中发挥着重要作用，而且对电信系统和卫星导航用户具有重要意义。现代社会越来越依赖于准确预测空间天气的影响，而实时监测电离层的电子分布及其不规则变化对于空间天气事件的预测和预警也至关重要。国际GNSS服务组织（International GNSS Service, IGS)实时性服务（Real-Time Service, RTS）的建立为GNSS全球电离层实时建模研究提供了重要契机，然而全球范围内可提供实时GNSS数据流的跟踪站的数量仍然较少，且分布不均匀，造成现有的全球电离层实时模型的精度和可靠性较低，无法满足精度需求。针对目前全球电离层实时模型精度和可靠性较低这一问题，本文构建了全球电离层垂直总电子含量（Vertical Total Electron Content, VTEC）短期预报模型作为全球的电离层实时建模过程中的数据补充，并在此基础上研究了基于GNSS实时VTEC观测值的数据附加策略，建立了GNSS高精度全球电离层实时模型，生成了更加稳定可靠的电离层实时产品。研究工作主要包括以下几个方面：

（1）首先基于经典的LSTM（Long Short-Term Memory）和ConvLSTM（Convolutional LSTM）深度学习方法构建了全球电离层VTEC短期预报模型，并分析了这两种经典方法在电离层VTEC短期预报中的优势与不足。然后在此基础上，基于这两种经典方法构建了LSTM+ConvLSTM电离层短期预报模型，并对这三种模型在不同地磁活动水平条件下的预报性能进行了评估。与LSTM和ConvLSTM单一模型相比，LSTM+ConvLSTM混合模型在磁暴期表现出更加优异的性能。

（2）与传统电离层实时产品直接将预报、快速或历史产品作为背景VTEC不同，本文在GNSS实时数据流的基础上，将全球电离层VTEC短期预报结果和欧洲定轨中心（Center for Orbit Determination in Europe, CODE）的快速电离层产品CORG一同作为全球电离层实时建模过程中的补充数据。研究了基于实时GNSS数据的实时全球电离层地图（Real-Time Global Ionosphere Maps, RT GIMs）的初步构建方法和短期预报VTEC以及CORG的虚拟数据附加策略，建立了基于实时数据流和虚拟附加数据的全球电离层实时模型，生成了最终的全球电离层RT GIMs产品。

（3）利用dSTEC检验、Jason系列卫星VTEC和与事后GIMs产品对比三种方式对本文生成的RT GIMs产品的精度进行了验证，并与其他各家电离层联合分析中心（Ionosphere Associate Analysis Centers, IAACs）的RT GIMs产品的精度进行了对比。结果表明，本文生成的XRTG产品的精度与CODE的事后产品CODG十分接近，优于其余的RT GIMs产品，且在强磁暴期的稳定性更强，性能更为优越。在海洋地区，XRTG的精度与CODG和西班牙加泰罗尼亚理工大学的实时产品UADG基本处于同一水平。与其他实时产品相比，XRTG与CODG更加接近，受磁暴的影响更小。

The ionosphere is an important part of space weather and the solar-terrestrial space environment. It not only plays an important role in trans-ionospheric radio propagation, but also has great significance for telecommunication systems and satellite navigation users. Furthermore, modern society relies more and more on accurately predicting the impact of space weather, and real-time monitoring of the electron distribution and its irregular changes in the ionosphere is also crucial for predicting and warning space weather events. The establishment of the real-time service (RTS) of the International GNSS Service (IGS) provides an important opportunity for GNSS global ionospheric real-time modeling research. However, the number of tracking stations that can provide real-time GNSS data streams around the world is still small and unevenly distributed, resulting in the low precision and reliability of the existing global ionospheric real-time models, which cannot meet the precision requirements. Aiming at the low precision and reliability of the current global ionospheric real-time model, this paper constructs a global ionospheric vertical total electron content (VTEC) short-term forecast model as a data supplement for the global ionospheric real-time modeling process. On this basis, the data addition strategy based on GNSS real-time VTEC observations is studied, a GNSS high-precision global ionospheric real-time model is established, and a more stable and reliable ionospheric real-time product is generated. The research work mainly includes the following aspects:

(1) First, based on the classic Long Short-Term Memory (LSTM) and Convolutional LSTM (ConvLSTM) deep learning methods, a global ionospheric VTEC short-term forecast model is constructed, and the advantages and disadvantages of these two classic methods in ionospheric VTEC short-term forecasting are analyzed. Then, on this basis, the LSTM+ConvLSTM ionospheric short-term forecast model was constructed based on these two classical methods, and the forecast performance of these three models under different geomagnetic activity levels was evaluated. Compared with the single model of LSTM and ConvLSTM, the hybrid model of LSTM+ConvLSTM shows better performance during the geomagnetic storm period.

(2) Different from the traditional ionospheric real-time products that directly use forecast, rapid or historical products as the background VTEC, this paper uses the global ionospheric VTEC short-term forecast results and CODE's (Center for Orbit Determination in Europe) fast ionospheric product CORG as supplementary data in the global ionospheric real-time modeling process based on GNSS real-time data streams. The primary construction method of real-time global ionospheric maps (RT GIMs) based on real-time GNSS data and the virtual data appending strategy of short-term forecast VTEC and CORG were studied. A real-time model of the global ionosphere based on real-time data streams and virtual data was built, and the final global ionosphere RT GIMs product was generated.

(3) The precision of the RT GIMs products generated in this paper is verified by using the dSTEC test, Jason series satellite VTEC and comparison with post-processed GIMs products, and compared it with the accuracy of RT GIMs products of other Ionosphere Associate Analysis Centers (IAACs). The results show that the precision of the XRTG product generated in this paper is very close to CODE's post-processed product CODG, which is better than other RT GIMs products and has stronger stability and superior performance during strong geomagnetic storms. In the ocean area, the precision of XRTG is basically at the same level as that of CODG and the real-time product UADG of the Universitat Politècnica de Catalunya (UPC). Compared with other real-time products, XRTG is closer to CODG and less affected by geomagnetic storms.

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