## 1 Introduction
The ARAIM algorithm in aviation has been adapted in recent years for ground-based applications such as road transport. The IM was performed, e.g., for PPP [19] and RTK [16; 20; 21]. The ARAIM algorithm used in aviation, however, is applied for single-receiver positioning. For the ground-based RTK positioning, more complicated multipath environments may need to be considered in the threat model, while the accuracy of the satellite clocks and orbits, which are important for the aviation ARAIM, do not play an important role for short-baseline RTK processing. In addition, the atmospheric residuals need to be considered at the between-receiver level. In this contribution, the analysis is performed for short baselines in atmosphere quiet days, so that the focus is on the multipath effects under different measurement scenarios. This leads to the second issue to be addressed in this contribution, i.e., determination of the overbounding mean and standard deviations for the between-receiver phase and code noise/biases under different measurement scenarios, which will be used for computation of the representative PLs during the IM.It is noted that during geophysical events like solar flare [22] and magnetic storms [23; 24], abnormal ionosphere behaviours may lead to enlarged differential ionospheric errors in the RTK processing. Note that this study is focused on short-baseline RTK positioning in quiet atmosphere conditions, and does not attempt to account for the RTK integrity monitoring under extreme atmospheric conditions. To solve this problem, the excess-mass cumulative distribution functions (EMCs) are searched for different observation types and measurement scenarios. In this contribution, the authors do not address the very challenging urban areas, which will be considered in future research, but put the focus on open-sky and suburban scenarios. In the presented IM approach, after applying the FDE procedure with the SST, utilising these overbounding mean and standard deviations, the horizontal protection levels (HPLs) are computed for the ambiguity-fixed solutions. Using the sequential exclusion method for ambiguity resolution as mentioned before, the proportion of the time epochs achieving full ambiguity resolution (FAR) is discussed for the open-sky and the suburban scenarios. The valid ambiguity-fixed HPLs are checked to bound the horizontal positioning errors (HPEs) and to be less than the horizontal AL (HAL). In addition, for the suburban scenario having more complicated multipath environments, investigations are also performed considering extra multipath biases for low-elevation rover phase observations. The resultant HPLs are compared with a set of different HALs that might be needed for different road transport applications. The paper starts with the signal analysis of different observation types under open-sky and suburban scenarios. The weighting model considering both the elevation angles and the C/N\({}_{0}\) is developed, and the coefficients leading to the largest positional benefits are given and used in the positioning and IM. The overbounding EMCs are then searched for the between-receiver mode for different observation types and various scenarios. Subsequently, the threat model, the FDE method, and the procedure to compute the HPLs are explained in detail. Test results based on real data are then analysed, where the positioning solutions, the HPLs and the HALs are discussed. The conclusions are then drawn.