一种区域精密天顶对流层延迟组合预报模型

针对现有区域天顶对流层延迟(ZTD)模型属于函数或格网型，参数固定，且难以表达ZTD时空快速变化特性等问题，提出一种基于小波变换、傅里叶级数拟合、自回归(AR)、支持向量回归(SVR)的组合预报新模型构建方法。该模型在时域内对ZTD序列进行小波变换，分解出低频和高频序列。低频序列采用傅里叶级数拟合成时间函数，高频序列则由AR进行预报。在空间域内利用SVR建立位置参数向傅里叶级数参数的映射。在该模型中输入时间与位置信息即可获取ZTD预报值。利用94个GNSS基站2 a的ZTD数据进行建模，24个GNSS基站1 a的ZTD数据进行预测对比。结果表明，实测值与模型预报值之间的平均偏差为-2.02 mm，均方根误差为3.07 cm，优于大部分区域ZTD模型。在伪距单点定位测试中，该模型能够显著提高定位精度。实验表明，该组合模型具有较高的预报精度和可靠性，具有一定的应用价值。

A Regional Precise Zenith Tropospheric Delay Combined Prediction Model

In view of the problems that the existing regional zenith tropospheric delay(ZTD) model belongs to function or grid type, the parameters are fixed, and it is difficult to express the characteristics of rapid spatio-temporal change of ZTD, we propose a new combined prediction model based on wavelet transform, Fourier series fitting, AR and SVR. In the time domain, the ZTD sequence is decomposed into low-frequency and high-frequency sequences by wavelet transform. The low-frequency sequence is fitted with Fourier series as a function of time, and the high-frequency sequence is predicted by AR. The mapping of position parameters to Fourier series parameters is established by SVR in spatial domain. Inputting time and location information in the model, the corresponding ZTD prediction value can be obtained. The two-year ZTD data of 94 GNSS stations are used for modeling, and one-year ZTD data of 24 GNSS stations are used for model prediction. The results show that the bias and RMSE between the measured value and prediction value is -2.02 mm and 3.07 cm, which is better than most of regional ZTD models. The model can significantly improve the positioning accuracy in pseudorange single point positioning. The experiments show that the combined model has high prediction accuracy and reliability, and that it has certain application value.