# Precise Positioning of BDS, BDS/GPS: Implications for Tsunami Early Warning in South China Sea
## 2 Real-Time Kinematic Precise Positioning Performance of BDS in South-East Asia  
Generally, there are two kinds of precise positioning algorithms, _i.e._, relative positioning and single-point positioning. With respect to relative positioning, most of the error budgets can be cancelled through double differencing between reference station and rover station; as a result, its mathematical model is relatively simple and easy to be conducted. Most importantly, double-differencing integer-cycle phase ambiguities can be resolved to their correct integer values, reliably ensuring its high precision. However, the reference station of relative positioning must be fixed, which requires that, during an earthquake, it should be located outside the zone of deformation. The latter cannot always be satisfied, especially during large tsunamigenic earthquakes [21]. By contrast, the single-point positioning approach does not need a fixed reference station to form double-difference observations and, in theory, is more desirable for the retrieval of co-seismic displacements [25]. Nonetheless, it should be pointed out that for Precise Point Positioning (PPP), ambiguity resolution needs a convergence phase that may be as long as 20 min. Fortunately, the Variometric Approach for Displacements Analysis Stand-alone Engine (VADASE) [39] and the Temporal Point Positioning (TPP) [40] are able to overcome this disadvantage. The TPP has been employed in this study. Up to now, no BDS or BDS/GPS data recorded during an earthquake is publicly available. Considering that performances of GNSS positioning are not different between earthquake-free and earthquake-breaking periods [13], to exploit the potential of BDS and BDS/GPS in retrieving co-seismic displacements, we selected two weeks of data (from 29 December 2013 to 11 January 2014) from IGS Multi-GNSS Experiment (MGEX) stations in the Asia-Pacific region. In this case, data from a 1-Hz sampling rate MGEX stations GMSD and SIN1 were used (see station distribution in Figure 1). Since no earthquake happened, we take zero displacement as ground truth. In this paper, real-time precise BDS/GPS orbits and clocks were produced according to the strategies suggested by [PERSON] _et al._[29]. For every station, the length of each TPP session was set to 10 min, and, in each individual hour, we employed four sessions with evenly distributed start points; in total, we have 96 sessions per day for two weeks, which ensures a more trustworthy conclusion on the precise positioning performance. Figure 2 presents the TPP results in modes of BDS-only, GPS-only and BDS/GPS at station GMSD which can be taken as a typical example. As clearly shown, BDS-only and GPS-only show similar positioning performances while a BDS/GPS combined solution significantly improves the accuracy. Statistical Root Mean Square (RMS) is summarized in Table 1. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**RMS (m)** & **BDS** & **GPS** & **BDS/GPS** \\ \hline East & 0.0095 & 0.0071 & 0.0049 \\ North & 0.0068 & 0.0101 & 0.0048 \\ Up & 0.0203 & 0.0207 & 0.0098 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Expected RMS of BDS, GPS, and joint BDS/GPS real-time precise positioning using TPP in South-East Asia. Testing the Feasibility of BDS Real-Time Network at the Luzon Island for the Tsunami Early Warning in the South China Sea  
In this section, we demonstrate the feasibility of BDS for the tsunami early warning in the Southern China Sea. To do that, we simulate a hypothetical tsunamigenic earthquake along the Manila trench and try to invert resulting co-seismic displacements at a virtual BDS/GPS array distributed along the Luzon Island, northern Philippines. Previously, [PERSON] [41] and [PERSON] _et al._[30] assessed tsunamigenic potential of six rupture scenarios along the Manila trench. We follow their approach and place our fault model along the northern part of the Manila subduction zone (Figure 1). Fault parameters correspond to the rupture model E2 from [PERSON] _et al._ (2006).