## 6 Conclusions  
This contribution presents the IM for ambiguity-fixed RTK solutions under different measurement scenarios. A weighting model allowing different impacts of the elevation angles and the C/N\({}_{0}\) is first developed. The weighting coefficients were searched for different measurement scenarios and observation types to minimise the influences of the biases on the positional results. Next, applying these weighting models, the overbounding mean and standard deviations are determined for the weighted between-receiver observations under the open-sky and suburban scenarios based on the overbounding CDFs.  
The IM is performed for RTK positioning using the ARAIM algorithm for real experiments resembling the open-sky and the suburban scenarios. After the FDE procedure, HPLs are computed for the ambiguity-fixed solutions and are compared with the HPEs and the HAL. Based on the sequential exclusion algorithm for ambiguity resolution, using GPS dual-frequency observations, FAR can be achieved in about 100% and 95% of the time for the open-sky and the suburban scenarios, respectively. Using the proposed weighting model and the mean and standard deviations derived from the overbounding EMCs, the ambiguity-fixed HPLs are at the sub-dm to dm-level. All valid HPLs are below the HAL of 0.5 m, and bound the ambiguity-fixed HPEs for both scenarios. The availabilities of the ambiguity-fixed horizontal positions reached 100% in both the open-sky and the suburban scenarios.  
Investigations were also performed for the suburban scenario with larger multipath. An extra bias of a quarter cycle was added for rover phase observations below an elevation threshold. It is shown that the mean HPL could be increased by above 40% when increasing this elevation threshold from 10 to 30 degrees. For applications with high accuracy requirements, i.e., with a HAL as low as 0.1 m, a dramatic decrease of the availabilities can be observed when increasing the elevation threshold.  
In more complicated measurement environments such as urban canyons, a weighting model related to both the elevation angles and the C/N\({}_{0}\) is also expected to behave better than that dependent solely on the elevation angles, as large multipath may appear also for signals of medium or high elevations. The bias behaviours of the DD phase and code measurements for RTK positioning in such environments, possibly not only collected from the geodetic receivers but also from low-cost receivers, will be investigated in future research.  
Figure 9: Change of (**a**) the mean and maximal HPLs and (**b**) the availabilities with the elevation threshold \(\tilde{\theta}^{\text{s}}\) for adding the phase bias term \(m_{c,k}\). The dataset in the suburban scenario during T1 is used for the computation.  
**Author Contributions:** [PERSON] and [PERSON] designed the research, [PERSON] analysed the data, [PERSON], [PERSON], [PERSON] and [PERSON] contributed to the writing of the paper. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research is funded by the ARC Discovery Project: Trustworthy Positioning for Next Generation Intelligent Transport Systems, Project ID: DP170103341. The open-access publication of this work is funded by the Research and Development Committee Small Grants Program, Faculty of Science and Engineering, Curtin University.  
**Acknowledgments:** We would like to thank the University of Western Australia for hosting the station UWA0. We also acknowledge Septentrio for providing the UWA0 receiver. The data for the tests were obtained from the GNSS Research Centre, Curtin University, via [[http://saegnss2.curtin.edu/ldc/](http://saegnss2.curtin.edu/ldc/)]([http://saegnss2.curtin.edu/ldc/](http://saegnss2.curtin.edu/ldc/)).  
**Conflicts of Interest:** The authors declare no conflicts of interest.