Zixi Liu, Sherman Lo, Todd Walter, Stanford University

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Abstract:

Automatic Dependent Surveillance – Broadcast (ADS-B) reports from aircraft have been examined by several groups for their capabilities to identify regions affected by radio frequency interference (RFI) [1] [2] [3]. RFI events that happen near airports could cause denial of GNSS based landings for aircraft and create a severe impact on the safety of aircraft operation during some vulnerable segments. Therefore, it is important to rapidly localize any GNSS interference sources and identify the geographical impact area. Using already existing aircraft reports of position from ADS-B is a highly desirable approach that could rapidly and inexpensively be implemented nationwide or even globally. This project has two main objectives. First, we developed a method of interference source localization which is applicable for different types of interference source using ADS-B data. Specifically, the mathematical model was designed without prior knowledge on the power level of RFI sources, making this factor as parameter to identify. Although this approach increases complexity, it allows our models to be more flexible and general. Second, we built an interference event simulator which generates ADS-B data from simulated aircraft flight tracks that may be affected by simulated RFI events. By building this simulator, we can then test our models for different scenarios including multiple jammers. Identifying and obtaining real-world ADS-B data from these types of events is difficult. Therefore, we rely on simulated data to better test our models for these special cases. To make the simulated data reasonable, our simulator also adds noise and includes erroneous outputs that we have observed during the investigation of real-world interference events.