This Ph.D. project is part of the CMC Electronics Industrial Research Chair on Resilient GNSS Navigation (GSDM). The research aims to advance the understanding of GNSS vulnerabilities to spoofing attacks and to develop innovative detection and mitigation strategies tailored to aeronautical and space applications. The Ph.D. candidate will contribute to the modeling, simulation, and experimental validation of anti-spoofing techniques integrated into hybrid GNSS receiver architectures (SDR, multi-constellation, multi-frequency).

Research objectives: • Develop an in-depth understanding of GNSS vulnerabilities to spoofing and jamming attacks. • Explore and evaluate major detection and mitigation (anti-spoofing) strategies, including cryptographic, signal processing, and sensor-fusion approaches. • Analyze and compare receiver architectures (traditional, SDR, multi-constellation) in terms of resilience. • Propose new GNSS/IMU fusion and machine-learning-based methods to enhance robustness and signal integrity. • Produce a comprehensive synthesis leading to the design of a resilient GNSS architecture suitable for aeronautical certification (DO-178C, DO-229).

Required profile: • Master’s degree in Electrical Engineering, Avionics, Computer Engineering, or a related field. • Strong interest in GNSS systems, cybersecurity, and signal processing. • Skills in deep learning, Kalman filtering, and multi-sensor data fusion. • Motivation for applied research and experimental validation.

Duration : 4 years (full-time)
Location : LASSENA Laboratory, École de technologie supérieure (ÉTS), Montreal
Chair presentation Video
Official Chair website : https://lassena.etsmtl.ca/chairecmc/
To apply: Complete the online form and include your CV, a cover letter, and, if applicable, your publications or relevant projects