# Characterization of Carrier Phase-Based Positioning in Real-World Jamming Conditions
## 6 Conclusions  
In this paper, three of the most severe incidents of jamming registered by the TAPAS network are analyzed. While no exact metric exists for determining the severity of a jamming incident, based on both duration and jamming strength, the three selected cases are once-in-a-year incidents.  
It was shown that single-baseline solutions based on a jamming-affected reference station may be severely affected, with errors up to several meters. Solutions based entirely on the affected frequencies and constellations are especially vulnerable.  
However, for positioning solutions based on several frequencies and constellations, errors outside the RTK norm (\(\pm\)5 cm) only occurred for a period of 1-2 min in just one of the three selected cases. Baseline length was shown to be irrelevant except for the extreme case of 61 km. Thus, multifrequency, multi-constellation solutions based on the TAPAS network are robust towards real-world jamming.  
It was further shown that carrier phase tracking in the reference station receivers is very reliable, and as long as the receiver tracks a satellite, it may be used for precise carrier phase-based positioning. In other words, only in severe cases, where C/N\({}_{0}\) ratio of a satellite is suppressed below the tracking threshold of 20 dBHz, will a satellite not provide reliable observation data. This supports observations made by [18].  
A similar conclusion may be made from the results of Analysis 2, which showed that the standard deviation of the carrier phase-based solution was basically unaffected by jamming (while a DGPS solution based on the same data was clearly degraded).  
Furthermore, none of the investigated incidents had any perceivable impact on the TAPAS network performance, nor the NTRK positioning solution.  
Thus, the conclusion is that a carrier phase-based solution using multi-frequency, multi-constellation observations from the TAPAS network is robust to jamming, and as an end user, one should only worry about interference on the rover end. This is, at least in part, due to the hardware and positioning of the reference receivers.  
Finally, while many of the results presented in Analyses 3, 4, and 5 are specific to this setup, and thus not reproduceable with other PPK software, it is clear that the processing method is important. If maximum robustness is the goal, the solution should not by default prefer some GNSS constellations or frequency bands over others. Instead, the solution should strive to dynamically select (or at least heavily emphasize) only the interference-free observations.  
[PERSON] drafted and edited the paper, and was responsible for all the research, experiment design, and analyses. [PERSON] and [PERSON] both provided supervision, and helped in planning the analyses and interpreting the results. All authors contributed to the reviewing of the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Data Availability Statement**: All data used for these experiments are gathered from the TAPAS testbed in Aarhus, Denmark, www.tapasweb.dk. The data are owned by the Danish Agency for Data Supply and Efficiency, SDFE, www.sdfe.dk, but are freely available, and may be requested by sending an email to [EMAIL_ADDRESS]. Access requires the signing of a user agreement with the SDFE.  
**Acknowledgments:** The authors would like to acknowledge the work of SDFE in establishing and maintaining the TAPAS testbed, and for their continuous support regarding any work relating to TAPAS. A special thanks also goes to Professor [PERSON] of the GEO department at DTU Space for his supervision and guidance both in the work related to this paper, but also in the general day to day tasks at the institute.  
**Conflicts of Interest**: The authors declare no conflict of interest.