Detection and Localization of Radio Frequency Interference Sources

This paper extends previous research on locating Radio Frequency Interference (RFI) sources using an Unmanned Aerial Vehicle (UAV) by enhancing the method’s accuracy and reliability. Building on earlier work, we introduce improvements in both hardware and algorithmic processing to ensure the system remains cost-effective, easily deployable, and operable by non-experts. A heading-capable GNSS receiver processes the signal from one of the two GNSS antennas through its primary port and a combined signal from a directional antenna and the second GNSS antenna through its secondary port. To prevent a loss of the GNSS heading due to strong RFI, we integrated a Micro-Electro-Mechanical Systems (MEMS) Inertial Measurement Unit (IMU) sensor to provide continuous heading information. We conducted flight tests to assess the system’s performance, using a 5G antenna as the interference source. The results demonstrate the IMU’s capability to bridge periods of GNSS heading loss, maintaining a deviation of 0.3 degrees. Additionally, we evaluated two methods for determining the bearing to the RFI source: one based on the C/N0 difference between the main and auxiliary GNSS antenna, and another relying only on the auxiliary antenna’s C/N0 values. The latter method proved more accurate, with a bearing estimate off by only 2.3 degrees from the true bearing of the UAV to the 5G antenna. Using two measurements, each consisting of a 360° rotation from different locations, the estimated RFI source location was determined. However, due to similar angles of both measurements towards the RFI source, it resulted in an error margin of 18.4 meters. The study concludes with recommendations for further refining the system, such as using a GNSS receiver with independent Automatic Gain Control (AGC) for each antenna input and conducting more extensive field tests with real jammers to evaluate the method’s efficacy at varying distances. Future work will also explore manual IMU calibration techniques to enhance heading accuracy in the absence of an initial GNSS heading calibration.