TDOA based ADS-B validation using a Particle Filter and Statistical Hypothesis testing

Abstract

ADS-B is a widely used protocol that transmits aircraft’s position, velocity among other data. The protocol is not encrypted leading to the need of validation. A validation algorithm is proposed that makes use of Time Difference of Arrival localization to validate the position and velocity of ADS-B transmitting targets. Nowadays, Air navigation service providers (ANSP) commonly have at least one TDOA localization system in operation, allowing for cost effective implementation. Validation is achieved by using a Particle Filter and hypothesis tests. A novel method is used where the initial density is generated effectively based on the first set of TDOA measurements. Validation is possible when two or more ground stations receive the same ADS-B transmission, therefore the Particle Filter is designed to process such measurements. The algorithm is tested on data provided by Air Traffic Control The Netherlands’ North sea surveillance system. Results show that the validation works and that the algorithm is able to detect spoofing. Based on spoofed ADS-B messages and true TDOA measurements, the real and fake target can be detected when the distance is roughly 750 to 1000 meters (depending on the situation and the various tuning parameters). In addition, validation based on two or more ground stations per measurements has the effect that the validation area is increased, when compared to traditional filters that require 4 ground stations for tracking.