# Evaluating GNSS Receiver Resilience: A Study on Simulation Environment Repeatability
## 6 Discussion  
A critical insight from our research is the significant and often overlooked unpredictability of GNSS receiver internal software in the context of jamming. Even when meticulous control over the input GNSS signal is achieved using calibrated sources in an attempt to isolate the receiver's pure response, this software, as it actively tries to mitigate interference and maintain accurate fixes, introduces inconsistencies. Our GNSS simulator tests clearly demonstrate this, revealing varying responses to identical, repeated signal inputs. Consequently, traditional jamming impact assessments, often lacking in statistical depth, fail to capture the intricate temporal dynamics of receiver behavior, particularly  
Figure 12: Performance comparison of the GP01, U-blox 6-Series, and U-blox 10-Series GNSS receivers under strong, three-frequency CW interference centered within the L1 band. Figure 13: Ublox-10 receiver performance under increasing CW interference power, illustrating the operational boundaries for response analysis. under conditions that do not lead to immediate failure. To truly understand these effects, especially in less severe jamming scenarios, extensive measurement repetitions (around 50 in our study) coupled with statistical analysis (median and standard deviation) are essential. This necessity only intensifies under real-world conditions where constantly evolving satellite geometry, multipath, scattering, and diverse, prolonged jamming events introduce even greater variability, demanding a statistically sound approach for meaningful evaluation. Our findings also reveal predictable trends: newer receiver generations, like the U-blox 10-series with its more sophisticated and evolved software, demonstrably handle interference far better than older models. This is evident in their ability to maintain near-full functionality even under stronger jamming levels compared to the U-blox 6-Series. Intriguingly, receiver responses still vary with interference type; for example, the 6 th generation U-blox is highly susceptible to mid-L1 band CW signals but more tolerant of wider FM interference. Conversely, the multi-constellation U-blox 10 th generation shows greater resilience to single-frequency CW, requiring substantially stronger interference to cause noticeable effects. While even the most advanced receivers will eventually fail under sufficiently strong interference, necessitating backup navigation, our results clearly indicate that utilizing newer generation multi-constellation and/or multi-frequency receivers offers significantly enhanced jamming mitigation capabilities compared to their predecessors. Although this work does not delve into specific mitigation strategies, the clear performance advantage of newer receivers like the U-blox 10 or Ai-Thinker GP-01 GP-01 underscores their importance in mitigating jamming effects. So, how should the assessment of jamming responses in GNSS receivers be approached? The findings highlight the inherent uncertainty in these responses, advocating for a more systematic investigative approach. By initially focusing on the software response as the sole variable, a baseline for understanding receiver behavior can be established. Subsequent studies can then incrementally introduce real-world complexities like dynamic satellite constellations, ionospheric effects, and environmental factors. Furthermore, long-term field data collection, spanning weeks and employing multiple receivers with consistent antenna setups, is essential for comprehensive analysis. Making the first steps in jamming assessment more accessible, we are publishing the extensive dataset generated during this research. This dataset, compiled over weeks using an automated laboratory setup, includes a multitude of receiver parameters (detailed in the linked public repository within the Data Availability Statement) and is provided as a valuable resource for the research community.