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Acta Geodynamica et Geomaterialia

 
Title: TIME SERIES ANALYSIS OF RADIO SIGNAL WET TROPOSPHERIC DELAYS FOR SHORT-TERM FORECAST
 
Authors: Rzepecka Zofia, Kalita Jakub Zbigniew, Stepniak Katarzyna and Wielgosz Paweł
 
DOI: 10.13168/AGG.2015.0031
 
Journal: Acta Geodynamica et Geomaterialia, Vol. 12, No. 4 (180), Prague 2015
 
Full Text: PDF file (1.0 MB)
 
Keywords: wet tropospheric delay, time series analysis, forecast, ARMA, ARIMA, power spectral density analysis, FFT, PPP
 
Abstract: The proposed short-term forecasting method bases on removing periodic signals basing on frequency analysis and then using modern tools of time series analysis on residuals. For this element the Auto-Regressive Integrated Moving Average forecasting model is used. The practical realization contains the analysis of tropospheric data obtained from the Vienna Mapping Function 1 service. The analysis contains time series data from four years (2010-2013) and two permanent stations located in Central Europe region. For both stations two main signals: annual and semiannual were removed using sine and cosine linear regression leaving residuals that still do not act as a white noise processes. For each of the analysed data sets appropriate parameters of the ARIMA model were evaluated and the accuracy of forecast values was analysed. The residuals of these expanded processes are white, therefore the estimated ARMA processes can be used for forecasting the future values. One-step forecasts based on the above models are estimated to be within ± 2.5 cm for 80% of confidence level and ±3.8 cm for 95% of confidence. Unfortunately, its confidence level quickly drops down, falling down to within ± 4 cm for the fourth forecasted epoch (four epochs completes 24h), at 80% of level of confidence.