一种用于中国地区的对流层天顶延迟实时修正模型

针对目前对流层延迟修正受限于探空数据不足导致修正效率低的问题，该文结合Saastamoinen和GPT2w模型构建形成组合模型Sa+GPT2w模型，通过利用GPT2w模型提供的高精度气象数据，实现中国地区对流层天顶延迟(ZTD)的实时修正，克服对探空数据的依赖，并用实测数据对计算结果进行验证。以IGS提供的中国地区2015至2017年ZTD时间序列为评估标准时，Sa+GPT2w模型(bias: 1.661 cm, RMS: 4.711 cm)的精度较同等条件下的Sa+EGNOS, Sa+UNB3m和Hop+GPT2w模型分别提升50.5%, 41.9%和37.1%；以GGOS Atmosphere 2017年ZTD数据为标准时，Sa+GPT2w模型(bias: 1.551 cm, RMS: 4.859 cm)的精度相对同等条件下的另3种模型分别提升49.5%, 38.5%和46.8%；最后对Sa+EGNOS, Sa+UNB3m和Sa+GPT2w模型在ZTD修正中误差结果的时空分布特征进行分析。研究结果可为在中国地区的导航定位、大气折射研究中，应用不同气象参数模型进行ZTD修正的有效性和可能达到的精度提供参考。

Real-time Correction Model for Zenith Tropospheric Delay Applied to the Chinese Region

In view of the correction for tropospheric delay is limited by the shortage of sounding data, which leads to the problem that the low correction efficiency, this paper proposes a model named Sa+GPT2w, combining Saastamoinen model with GPT2w model. In this paper, the real-time correction for Zenith Tropospheric Delay (ZTD) over China is realized by using the high-precision meteorological values provided by the GPT2w model, and the results are verified by the measured data. Taking the ZTD in 2015-2017 of International GNSS Service(IGS) as a reference, the accuracy of the Sa+GPT2w model (bias: 1.661 cm, RMS: 4.711 cm) rises by 50.5%, 41.9% and 37.1%, respectively, relative to the Sa+EGNOS, Sa+UNB3m and the Hop+GPT2w models. Moreover, using the ZTD from Global Geodetic Observing System (GGOS) in 2017 as a standard, the Sa+GPT2w model (bias: 1.551 cm, RMS: 4.859 cm) improves the accuracy by 49.5%, 38.5% and 46.8% relative to other three models, respectively. Finally, this paper analyzes the temporal and spatial distribution characteristics of the bias and RMS of the above three models. The results provide a significant reference for the effectiveness of correction for ZTD by using different meteorological models in the research of navigation and atmospheric refraction over China.