## 5 Test Results  
The baselines UWA0-CUT0 and UWA0-SUB0 (Figure 1) were used for the tests in the open-sky and the simulation of suburban scenarios, respectively, based on 1 Hz GPS data. To test the positioning behaviours under different satellite geometry conditions, two time periods were used for the analysis, i.e., 0:00:00-6:56:01 (GPST) on 17 October 2019, denoted as T1, and 11:00:00-18:02:39 (GPST) on 16 October 2019, denoted as T2. Applying the weighting model for the open-sky scenario, the average PDOPs amount to about 3.5 for T1, and about 3.0 for T2. The elevation-dependent and C/N\({}_{0}\)-dependent weighting functions, which show the best behaviours in Table 2, are used for the analysis for the two measurement scenarios. The signal standard deviations obtained with the sequential LS-VCE method (Section 2.2) and the overbounding mean and standard deviations (Section 4.1) were used for computing the positions and the protection levels, respectively. Although the rover receiver in the test of the suburban scenario is surrounded by metal infrastructure and trees as shown in the middle and right panels of Figure 1, integrity monitoring of the RTK positioning in more challenging environments, e.g., urban areas, and in kinematic mode are of interest for road transport users. These scenarios may involve more complicated and fast changing multipath environments. They are not attempted in this contribution, but are expected to be addressed in future studies. Figure 7 shows the positioning errors in the horizontal plane and in the vertical direction for both the open-sky and the suburban scenarios. A larger error scatter can be observed for the suburban scenario. The ambiguity-fixed HPEs, computed as the square root of the squared sum of the ambiguity-fixed north and east component positioning errors, and the corresponding HPLs (Equation (56)) are shown in Figure 8 for T1 with higher PDOP as an example for the worse case among the two tested time periods. The ambiguity-fixed HPEs, computed as the square root of the squared sum of the north and east positioning errors, and the corresponding HPLs are shown as blue and green dots, respectively. A HAL of 0.5 m (red dots) is assumed for both scenarios. The statistics of the HPEs and the HPLs are given in Table 5 for both T1 and T2. As shown in the Table 5 and Figure 8, the FAR is achieved in the open-sky scenario for almost all time epochs for both time periods. In the suburban scenario, the FAR is achieved in about 95% of the time for T1 and almost 100% for T2. For time epochs having PAR, the majority of the ambiguities are also resolved with an average proportion of above 90% among all the ambiguities. The RMS of the HPEs are at the cm-level in both scenarios with the ambiguities fixed. Although the HPLs in the suburban scenario are higher than those in the open-sky scenario, they are generally at the sub-dm to dm-level. The ambiguity-fixed HPLs always bound the corresponding HPEs, and are always bounded by the HAL of 0.5 m. This leads to an availability of 100% for both measurement scenarios for T1 and T2. Figure 7: Ambiguity-fixed positioning errors in (**a**) the horizontal plane and (**b**) the vertical direction during T1 for the open-sky and the suburban scenarios. In more complicated suburban environments, larger multipath could exist in the measurements and hence bias the positioning results. For ambiguity-fixed solutions, the focus of the investigation is on the phase multipath, as the code observations are largely down-weighted, and very large code multipath is assumed to be detected by the FDE procedure. As the phase multipath should not exceed a quarter cycle [47], an extra bias of 0.25 cycle is assumed for the rover phase observations \(\Delta\phi^{s}_{j}\) (s \(\
eq\) 1) under an elevation threshold, denoted as \(\bar{\theta}^{s}\).