Investigation of GPS Interference Events with Refinement on the Localization Algorithm

Abstract

. ABSTRACT GNSS serves safety-of-life applications in aviation such as precise navigation for approach and landing operations. Interference events happen near airport can severely affect the safe operations of the airspace. A recent interference event happened at Dallas-Fort Worth International Airport (KDFW) in October/2022 caused a widespread disruption. This incident resulted in multiple aircraft reporting GPS unreliable within 40NM, closure of a runway, and rerouting of air traffic. In this study, we performed a detailed investigation on this event, and run our localization algorithm to provide an initial estimation of the potential jamming source. There were no public reports from ground infrastructures during this event, which means collecting data from the ground is not sufficient. Therefore, in this study, we used data collected from Automatic Dependent Surveillance—Broadcast (ADS-B) system. It is a satellite-based surveillance system on the airplane which broadcasts aircraft position information. ADS-B is already widely in use and was made mandatory in Europe and the U.S.A. by 2020. This ubiquity and openness of ADS-B provides widely available source of GNSS information. In addition to investigating Dallas event, this research also built on our previous work on localizing interference sources (Liu et al., 2022) and provided a method to calculate an error bound on the final estimated jammer location. In our prior research, we built an algorithm that can identify the most likely location and transmitted power of potential jammer in real time. In this work, we designed an algorithm to provide real-time confidence information about the localization result. The error bound calculated from this confidence monitoring scheme is compared with result from the bootstrap method (Stine, 1989).