Global GNSS Interference Detection and Impact Analysis for Aviation Safety

Global navigation satellite systems have significantly improved aeronautical navigation over the past decades, providing a safe and precise means of navigating airspace. Unfortunately, recent years have seen a worrying increase in GPS interference incidents in aviation, which is alarming because GPS is crucial for modern aviation navigation and safety. GPS interference, through jamming and spoofing, can lead to navigational errors, increased risk of accidents, and compromised air traffic control. IATA’s Global Aviation Data Management (GADM) team is preparing reports on GPS signal loss using data from the Flight Data Exchange (FDX) program to address this. They plan to extend their analysis globally using ADS-B data to identify safety issues. Various methods, including statistical analysis, software-defined radios, and machine learning algorithms, are being explored to detect GNSS jamming and spoofing. Long Short-Term Memory (LSTM) networks are particularly effective in modelling aircraft trajectories using ADS-B data because they can handle sequential data over long periods. This project aims to improve the detection of GNSS interference by applying advanced machine-learning techniques to global ADS-B data. The GADM team will provide a secure data-sharing environment, and ETS researchers will implement methodologies to detect interference patterns, enhancing aviation safety.

Faculty Supervisor:

Julio Montecinos;Georges Ghazi;Mustapha Ouhimmou

Student:

Partner:

International Air Transport Association

Discipline:

Engineering

Sector:

Other services (except public administration); Professional, scientific and technical services; Transportation and warehousing

University:

École de technologie supérieure

Program: