For those who have installed a Matlab on their computer, the program can be invoked by typing "run SSA_PV1.p" or “run SSA_PDV1.p” in the command window. Before the computation is started, a file named “InputFiles” containing a list of GPS data files to be processed needs to be prepared. All the files including "SSA_PV1.p","InputFiles" and GPS time series files need to be put into one folder.
We have provided some examples in the folders “SSA-PD” and "SSA-P" for the preparation of the user's own GPS data for processing.
As stated in the paper, SSA-PD has a very good performance in fitting the GPS time series containing offsets, non-linear trend or periodic components with time-varying amplitudes. However, the accuracy of the prediction results from SSA-P will decrease with time and also will be affected by the location of the offsets. Therefore, to obtain a better prediction results the users need to correct the offsets in the time series before adopting SSA-P for predicting the coordinates. We are currently working on a new version of SSA-P to further improve its performance .
Another software package (developed by Anton et al.) based on SSA for decomposition, forecasting and gap-filling for univariate and multivariate time series can be found at https://cran.r-project.org/web/packages/Rssa/index.html. More information about this software package is avaialbe at at http://www.sciencedirect.com/science/article/pii/S0167947313001394.