In this work, we argue that current state-of-the-art methods of aircraft localization such as multilateration are insufficient, in particular for modern crowdsourced air traffic networks with random, unplanned deployment geometry. We propose an alternative, a grid-based localization approach using the k-Nearest Neighbor algorithm, to deal with the identified shortcomings. Our proposal does not require any changes to the existing air traffic protocols and transmitters, and is easily implemented using only low-cost, commercial-off-the-shelf hardware. Using an algebraic multilateration algorithm for comparison, we evaluate our approach using real-world flight data collected with our collaborative sensor network OpenSky. We quantify its effectiveness in terms of aircraft location accuracy, surveillance coverage, and the verification of false position data. Our results show that the grid-based approach can increase the effective air traffic surveillance coverage compared to multilateration by a factor of up to 2.5. As it does not suffer from dilution of precision, it is much more robust in noisy environments and performs better in pre-existing, unplanned receiver deployments. We further find that the mean aircraft location accuracy can be increased by up to 41 in comparison with multilateration while also being able to pinpoint the origin of potential spoofing attacks conducted from the ground.
Overall, the main (distributed) localization approach used within aviation is MLAT @cite_11 , which we discuss in detail in the next section and which provides the baseline for our evaluations. To the best of our knowledge the combination of the k-NN algorithm with TDoA as a primitive has not been studied. In the following, we argue that this combination is beneficial in particular for crowdsourced networks with random, imperfect system geometry in which the performance of MLAT suffers strongly.
@cite_11
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Air traffic is continuously increasing worldwide, with both manned and unmanned aircraft looking to coexist in the same airspace in the future. Next generation air traffic management systems are crucial in successfully handling this growth and improving the safety of billions of future passengers. The Automatic Dependent Surveillance Broadcast (ADS-B) system is a core part of this future. Unlike traditional radar systems, this technology empowers aircraft to automatically broadcast their locations and intents, providing enhanced situational awareness. This article discusses important issues with the current state of ADS-B as it is being rolled out. We report from our OpenSky sensor network in Central Europe, which is able to capture about 30 percent of the European commercial air traffic. We analyze the 1090 MHz communication channel to understand the current state and its behavior under the increasing traffic load. Furthermore, the article considers important security challenges faced by ADS-B. Our insights are intended to help identify open research issues, furthering new interest and developments in this field.