【摘要】 为了提高无气象条件下对流层延迟预测的精度,提出一种基于小波及自回归方法(WAMIX)的预测模型:选用IGS站天顶对流层延迟产品建模;经谐波函数提取长周期项后,对其残差序列进行小波分析,分解成低频信号和高频噪声分量;然后对低频信号建立自回归模型,并联合谐波拟合及AR模型实现对流层的预测;最后以7个IGS站的ZTD为真值,对比分析WAMIX、GPT2w和IGGtrop_SH 3种模型30 d的预测精度。实验结果表明,WAMIX比另外2种模型的预测精度更高。更多还原

【Abstract】 In order to improve the prediction accuracy of tropospheric delay without meteorological data, the paper proposed a prediction model based on wave-autoregressive method: the zenith tropospheric delay(ZTD) product of IGS station was used to establish the model;after extracting the long-period term by the harmonic function, the residual sequence was analyzed with wavelet method to be decomposed into low-frequency signals and high-frequency noise components; then the autoregressive model was established for the low-frequency signals, and the tropospheric prediction was realized by integrating harmonic fitting with AR model; finally the ZTD of 7 IGS stations was taken as the true values, and the 30-day prediction accuracy of the three models of WAMIX, GPT2 w and IGGtrop_SH was contrasted and analyzed. Experimental result showed that the prediction accuracy of WAMIX would be better than that of two other models.更多还原