# GPS Time Series Analysis from Aboa the Finnish Antarctic Research Station
## 2 Materials and Methods
### Data Processing  
GPS observation data for high-precision applications are typically processed based on two basic approaches: relative positioning and point positioning. Relative positioning allows estimating the position of a new point with respect to another known, reference point [45; 46]. Baseline between a pair of points is observed and processed by forming double-differenced (DD) code and phase observations and solving for the integer phase ambiguities. DD approach (i.e., difference between-receivers and between-satellites) removes the observation errors common to both ends of the baseline, such as satellite orbital errors, satellite clock biases and receiver clock biases. In addition, errors due to troposphere and ionosphere reflection are eliminated or mitigated due to the correlation with the distance between the two points. The longer the distance, the higher the residual errors. Therefore, relative positioning may be extended to a local or regional network. However, the approach becomes computationally cumbersome if the number of stations within such a network increases significantly [27]. Precise Point Positioning (PPP) [47] uses un-differenced, dual-frequency, code and phase observations from a single user receiver along with precise satellite orbit and clock products. The dual-frequency observations are used to form ionosphere-free linear combinations in order to remove the first order ionospheric effects. Unlike in DD relative positioning, PPP has no baseline constraint and thus does not require simultaneous observations at two points. Although PPP itself uses data from a single station only, computation of the satellite orbits and clocks needed for its implementation require the use of a global tracking network [48]. Moreover, PPP requires more careful handling of all error sources affecting the satellite observations than DD relative positioning [49; 50]. Furthermore, the physical models (e.g., Earth tides, antenna phase centre corrections) used in the PPP processing should be consistent with those used in the generation of the precise products. Figure 3: Yearly distribution of the daily observation files logged at Aboa between 1 February 2003 (2003–032) and 8 December 2017 (2017–342). The parameters estimated with PPP processing are the 3D point position, the receiver clock, the zenith tropospheric delay and the non-integer ambiguity for each satellite. PPP positions are computed directly in the terrestrial frame in which the satellite orbits and clock parameters are given [27]. The current frame realisation is International Terrestrial Reference Frame (ITRF) 2014 [51]. A variety of tools for precise GPS/GNSS observation data processing have been developed at academic, research, and commercial institutions. They may be grouped into scientific, commercial and open-source software packages. In addition, numerous free online and commercial services exist. Table 1 summarises the most common GPS data processing packages and services. In this work, we chose the PPP approach instead of the DD to estimate station velocities independently of the other stations' data. The DD solution would be strongly dependent of the reference velocities of the sparsely located ITRF stations and also affected by the data quality of the reference stations. Our PPP daily positions at Aboa were estimated using the following two tools: RTKLIB open-source package ([[http://www.rtklib.com/](http://www.rtklib.com/)]([http://www.rtklib.com/](http://www.rtklib.com/))) and Automatic Precise Positioning Service (APPS) web-service ([[http://apps.gdgps.net](http://apps.gdgps.net)]([http://apps.gdgps.net](http://apps.gdgps.net))), respectively. The former is a versatile tool that enables scientific processing of the data via numerous parameters, some with default values. Nevertheless, the tool requires a high level of understanding of the processing engine to exploit its potential and flexibility. On the other hand, APPS is an easy to use web service based on the GIPSY processing engine.