Development of a GNSS Resilience Grading and Certification System (MSc/PhD)
Objective
Design and implement a standardized testing and certification framework capable of evaluating the resilience of GNSS-based Positioning, Navigation, and Timing (PNT) systems against jamming, spoofing, meaconing, and advanced interference threats.
Project Overview
This project will establish the first comprehensive GNSS Resilience Grading System, enabling objective, repeatable, and traceable assessments of receiver robustness under controlled threat scenarios. The resulting framework will support aviation, autonomous vehicles, defense, and critical infrastructure sectors by providing performance evaluations aligned with emerging international safety and integrity standards. This work will help shape future certification practices for resilient PNT technologies in Canada and globally.
Key Responsibilities and Activities
- Develop a threat-scenario library encompassing realistic and laboratory-reproducible attack vectors (jamming, spoofing, meaconing, multi-vector interference).
- Design quantitative scoring algorithms using KPIs such as detection probability, false-alarm rate, protection-level degradation, reacquisition time, continuity risk, and safe-mode transitions.
- Implement automated testing workflows using GNSS simulators, SDR platforms, and hardware-in-the-loop (HIL) environments.
- Benchmark and validate the grading system across commercial, aerospace-grade, and research receivers.
- Produce certification-style assessment reports containing traceable metrics, resilience grades, and improvement recommendations.
Required Skills and Background
- Solid understanding of GNSS signal structures, receiver processing, and PNT fundamentals.
- Experience with SDR development or hardware-in-the-loop testing environments.
- Knowledge of GNSS vulnerabilities, spoofing/jamming mechanisms, and modern countermeasures.
- Familiarity with aviation and safety-critical standards (DO-229D, DO-178C, DO-254, RTCA interference guidelines).
- Experience with GNSS simulators (e.g., Spirent, Safran) is an asset.
- Experience with programming and data analysis using Python, MATLAB, and/or C/C++ for algorithm development.
Deliverables
- GNSS Resilience Validation Framework.
- Threat scenario database and test configuration specifications.
- Scoring methodology and certification criteria documentation.
- Comparative performance evaluation of multiple GNSS receivers.
- Recommendations for improving receiver robustness based on empirical findings.
👉 Apply here:https://lassena.etsmtl.ca/join-us/
