1. Introduction
In the previous section, it was demonstrated that the examined flight events took place under different geomagnetic conditions.
In the following, we examine how these differences may manifest in the operation of GNSS-based systems and how they can influence drone flight stability in practice.
2. NOAA and the Interpretation of Geomagnetic Activity
Based on available data sources for the examined period, the Kp ≈ 6 value measured on June 7, 2024 corresponds to a moderate geomagnetic storm (G2) according to the NOAA scale.
In contrast, the Kp ≈ 1 value observed on June 13, 2024 indicates a quiet geomagnetic environment, which, within this interpretative framework, is not considered critical for the operation of satellite navigation systems.
In the period following the June 13 event, no significant geomagnetic disturbance was observed. Kp index values showed a gradual increase; however, these changes fall within the range of normal geomagnetic fluctuations and do not indicate the development of a geomagnetic storm.
The NOAA classification makes it possible to interpret measured Kp index values directly in terms of their expected practical impacts.
2.1. What Does This Mean from a GNSS Perspective?
During the operation of GNSS systems, the stability of position determination directly depends on the quality of incoming satellite signals. In the presence of geomagnetic activity, changes occurring in the ionosphere can affect the predictability of signal propagation, which may appear as positioning inaccuracies and temporal position fluctuations.
This is particularly relevant in applications where GNSS data directly influence system behavior. In the case of multirotor drones, position holding and stabilization are based on continuously updated GNSS positions; therefore, any fluctuation may also manifest during flight.
It is important to emphasize, however, that no direct cause-and-effect relationship can be established between geomagnetic activity and flight instability. In this context, the geomagnetic environment should rather be interpreted as a background factor that may, under certain conditions, contribute to uncertainty in the operation of GNSS-based systems.
2.2. GNSS Signal Quality and Ionospheric Effects in More Detail
From the perspective of GNSS signal quality, the state of the ionosphere plays a key role, as radio signals propagate through this layer. The electron content of the ionosphere – often characterized by the Total Electron Content (TEC) value – has a direct effect on signal delay.
In addition to the general effects described earlier, the following phenomena are particularly relevant from the perspective of practical GNSS-based applications, especially in drone and RTK-based systems.
During geomagnetic activity, the structure of the ionosphere may become unstable, leading to the following phenomena:
- ionospheric scintillation (amplitude and phase fluctuations of the signal) – the strength and phase of GNSS signals change rapidly, which may result in uncertain positioning and temporary signal loss
- GNSS signal loss or short interruptions – the satellite signal may temporarily disappear, causing gaps in position updates or the use of erroneous data
- increased position scatter – a wider dispersion appears around the calculated position, meaning the drone may move within a broader area on the map even if it is actually hovering near the same location
- instability of RTK fixed solution – the high-precision RTK solution may be lost or switch to a “float” state, resulting in sudden accuracy degradation and unstable position holding
These effects can be particularly critical during low-altitude operations requiring high positional accuracy.
2.3. What Does This Mean During a Drone Flight?
Most multirotor drone flight control systems use GNSS-based positioning for stable hovering, position holding, or accurate execution of automated flight paths. If GNSS position quality degrades, the system may:
- receive less accurate or noisier position data
- perform more frequent and larger corrective actions
- experience unstable position holding
- in extreme cases, switch to ATTI mode or exhibit drift
However, this does not automatically mean that a given event was caused by space weather. Flight stability can be influenced by many other factors, such as:
- GNSS signal obstruction (buildings, structures)
- multipath signal propagation
- sensor errors
- compass or IMU deviations
In this context, space weather should be considered a possible background factor that, under certain conditions, may contribute to the degradation of GNSS signal quality and thereby indirectly influence flight stability.
3. Two Events, One Question
The two presented flight events occurred close to each other in time, which justifies examining external environmental factors, including the state of the ionosphere.
However, the objective of this article is not to determine a single triggering cause, but rather to interpret the technical events within a broader context and to identify factors that may influence the operation of GNSS-based flight systems.
3.1. Conclusions
Based on the analysis of the two cases, it can be concluded that the observed phenomena were not clearly caused by a technical malfunction; in other words, the drone itself was not fundamentally faulty, but some external factor may have influenced the events.
In the first case (June 7, 2024), minor instabilities and drift phenomena were already observable during the flight. Despite this, the system completed the automated survey and initiated the return to the take-off and landing point. At the end of the process, however, a sudden total signal loss occurred, preventing the remote pilot from intervening, even after detecting the issue. As a result, the UAS crashed and all communication was lost. It is important to emphasize that the total signal loss was not caused by a battery failure, and this possibility was clearly ruled out.
It should also be noted that, based on the available data, no single clear triggering cause could be identified. However, due to the nature of the sudden signal loss, it cannot be excluded that temporary degradation of GNSS signal quality may have played a role. Space weather effects – particularly geomagnetic activity and ionospheric disturbances – may, under certain conditions, contribute to uncertainty in GNSS-based system operation; however, in this case, they can only be interpreted as a possible background factor.
In the second case (June 13, 2024), the flight initially appeared completely normal: the system was performing its task without any error messages, and all operations seemed appropriate. During the agricultural survey, however, the drone unexpectedly switched to ATTI mode without pilot intervention, a mode of operation previously described in detail.
In this flight mode, the system does not maintain GNSS-based position holding, resulting in significantly reduced stability and immediate onset of drift. Handling such situations is inherently difficult and requires considerable pilot experience, especially when the drone is at a greater distance. This is a higher-risk flight mode, which is also included in practical examinations within the specific operational category to ensure that remote pilots can demonstrate their ability to handle such situations.
In this case, the mode switch occurred during an automated operation without the pilot’s intention, and the response may have been delayed due to distance or momentary attention levels. After the onset of drift, it is evident that the pilot attempted corrective inputs via the controller; however, the drone became completely unstable, performed several uncontrolled maneuvers, and ultimately crashed. The logs do not indicate that the pilot attempted to switch back to GPS mode.
In this second case as well, the pilot appeared to have no realistic opportunity to recover the operation or save the drone.
In both cases, it is important to emphasize the need to prepare for such unexpected events. Fortunately, the examined operations were conducted outside populated areas, and appropriate ground and air risk buffer zones were established, so no personal injury or third-party damage occurred. These events highlight the importance of emergency procedures, especially in higher-risk operations, including those conducted in populated areas, where the goal is at least to mitigate the consequences of such incidents.
At the same time, it is evident in both cases that the pilots were practically unable to intervene at certain stages of the events. This is particularly concerning given that, based on checklists, the systems were properly maintained and prepared for operation, suggesting that everything appeared to be functioning correctly.
It cannot be excluded that human factors also contributed to the events. Since these operations are performed multiple times daily in the given area, it is possible that pilot attention was not always at an optimal level. In such situations, delayed reactions may further increase risks. Although this aspect was not examined in detail in the present analysis, its influence cannot be ruled out.
4. Practical Approach and Forecasting
4.1. Data Source and Background
The Kp index data used in this analysis originate from the planetary Kp index archive operated by the GFZ German Research Centre for Geosciences.
GFZ Potsdam is one of the most important international data centers for geomagnetic activity, calculating and publishing standardized Kp index values based on data from multiple ground-based observatories.
These data are widely accepted in both scientific and operational contexts, providing a reliable basis for analyzing geomagnetic activity.
4.2. Forecasting Possibilities and Practical Application
The analysis of geomagnetic activity is not only relevant for retrospective evaluation but may also be useful during flight planning.
Today, several forecasting systems and applications are available that allow pilots to assess expected geomagnetic conditions based on current solar activity.
One such example is the UAV Forecast mobile application, which provides both current and forecasted Kp index values, thereby supporting flight-related decision-making.
Additionally, the NOAA Space Weather Prediction Center offers short- and medium-term geomagnetic forecasts, which can help identify certain risks in advance.
It is important to emphasize, however, that these tools serve as supplementary information and do not replace the comprehensive evaluation of local conditions and the operational environment.
Considering geomagnetic activity can therefore represent an additional factor contributing to more informed risk management in drone operations.
The presented cases clearly demonstrate that anomalies observed during drone flights are not always the result of obvious technical failures.
Although the influence of space weather cannot be definitively proven as a direct cause, under certain conditions it may contribute to uncertainty in GNSS-based system performance, thereby indirectly affecting flight stability.
In practice, this means that taking such environmental factors into account is becoming increasingly important for safe and responsible drone operations.
Sources: