# Preliminary Results on Tropospheric ZTD Estimation by Smartphone
## 2 Materials and Methods
### Case Study: Materials, Methods and Processing  
The Broadcom 47/55 dual-frequency GNSS chip embedded in Xiaomi Mi8 smartphones was considered for these tests. It is capable of tracking GPS L1 C/A, GLONAES L1, BeiDou (BDS) B1, QZSS L1, Galileo (GAL) E1, GPS L5, Galileo E5a, and QZSS L5 signals. Regarding the geodetic receivers, two GNSS CORSs were considered to guarantee the highest quality in terms of collected signals and frequencies, as well as the number of tracked satellites.  
Two different types of software have been employed and considered for this work: the CSRS-PPP and a modified version of RTKLIB 2.4.3 b33.  
CSRS-PPP is an online application for GNSS data post-processing, allowing users to compute higher accuracy positions from their raw observation data. CSRS-PPP uses precise GNSS satellite orbit ephemerides to produce the corrected coordinates of a user located on a generic point, regardless of proximity to available base stations. The software can process RINEX observation data from single or dual-frequency receivers operating in static or kinematic mode. CSRS-PPP uses the best available ephemerides, and it allows the users to select final (\(+/-2\) cm, combined weekly and available 13-15 days after the end of the week), rapid (+/\(-\)5 cm, available the next day), or ultra-rapid (+/\(-\)15 cm, available every 90 min) ones, as it is possible to see in the specific IGS website section [50]. With the new version, the software includes PPP with ambiguity resolution (PPP-AR) for data collected on or after 1 January 2018. The output of the processing is sent to the user in a compressed folder. In particular, a tropospheric zenith delay file (with.tro extension) is created, containing hydrostatic and wet zenith path delays and tropospheric gradients for each processed epoch. For all measurement campaigns considered in this research activity and all the employed receivers, the following parameters have been selected for the data processing, considering the CSRS-PPP software: a cut-off angle equal to 7.5\({}^{\circ}\), the Vienna Mapping function as the a priori tropospheric model, and the a posteriori variance factor used to scale the covariance matrix equal to 1.  
RTKLIB is an open-source software widely used by both the academic community and other interested parties. The version considered in this paper is based on an Extended Kalman Filter (EKF) employing Zero-Difference (ZD) measurement equations, such as single point positioning, but also considering the receiver and antenna Phase Center Variations (PCVs), to take into account the Phase Center Offset (PCO), defined as the relative position of the receiver antenna phase center with respect to the antenna reference point (ARP). In this research activity, the ANTEX format for the antenna model, including PCO and PCV data, has been considered and used. Even for the RTKLIB software, the cut-off angle was defined as 7.5\({}^{\circ}\); by using the typical EKF formulation, the unknown parameters, including the receiver position and velocity, the receiver clock bias, the troposphere parameters and the ionosphere-free LC, and carrier-phase biases are estimated. For this work, the RTKLIB version, solid earth tides, Ocean Tide Loading (OTL), and pole tides are modelled and properly considered, the same as for the CSRS-PPP software. In both cases, precise ephemerides and clocks have been used considering MGEX products [51; 52], as well as the PPP-AR algorithms as the ambiguity resolution method. To weight the observations, SNR values have been selected. For both types of software, the final solutions have been considered in the ITRF realization to be compliant with the GNSS processing products (e.g., ephemerides, ocean tide loading), considering a forward solution based on EKF.  
Table 1 summarizes the processing settings for both of the considered software. It is important to highlight the fact that the duty cycle was disabled for all the data collected in the two campaigns.