The intense use of the 2.4 GHz ISM band by several wireless technologies has resulted in increased co-channel interference between networks operating in this frequency band. The aim of this paper is to investigate modeling techniques of co-channel interference affecting bluetooth low energy devices. The models are derived from recorded interference. Two types of models are introduced: a time domain model utilizing IQ data as reference and a spectrum-based model in which the reference signal is captured in frequency domain by a real-time spectrum analyzer. The recorded interference is also used as a reference to analyze the accuracy of proposed models. The proposed IQ-based model shows a degradation in performance for the environments with dominant bluetooth interfering signals. The frequency-based model not only addresses this problem, but also results in a huge data decimation in recording the interference.

Intentional and unintentional GNSS interference can greatly affect the performance of precise timing and localization in areas such as automated driving or aviation. Nevertheless, reports show that jamming occurs near many European airports that are located close to a highway or in heavy industry areas due to broadcasting of interfering signals. To assess the impact of such potential risks, we investigated interference occurring on a section of highway located both near to an airport and close to logistics centers as part of the Austrian Security Research Program project CATCH-IN. This section of highway is of particular interest, as the highway runs in parallel to the approach path of aircraft and crosses the approach path 3.7 km before the aircraft touches down (the flight altitude is only 200 m above the ground). For this experiment, we distributed six Septentrio Mosaic x5 GNSS receivers as sensors along the highway and monitored this section for five months. We analyzed the data with AGC monitoring, CN0 monitoring, and baseband sample monitoring to identify interference along the highway that could affect sensors along the descending flight trajectory. During the period of this experiment, we saw events that we believe could cause potential safety risks and problems for aviation safety. In our analysis, we focused on the statistical evaluation of the temporal repetitions, in particular the times of day that see more interference and the frequencies at which more interference occurs. Additionally, we analyzed the performance of different algorithms for dealing with large datasets. The results provide new insight into potential monitoring stations near airports and raise awareness of potential risks and vulnerabilities in aviation safety as well as automated driving along highways.

GNSS-based navigation is commonly used in aircraft as a source of localization. As reports of pilots about jamming during flights are becoming more frequent, we performed jamming tests with a parked passenger aircraft to assess the criticality of jamming events. We observed the reaction of the aircraft GPS position display in the cockpit and the ADS-B availability during jamming. We analyzed the relative power levels at which the GPS-receivers and the ADS-B broadcasting show negative effects. Beyond other factors, we observed significantly long recovery times for the GPS position display and the ADS-B system. The results give unique detailed facts about the vulnerability of one type of commercial passenger aircraft and emphasize how important it is to raise awareness of this vulnerability in aviation.