In this work, we propose an innovation-based INS spoofing monitor that utilizes a tightly-coupled INS-GNSS integration in a Kalman filter. The performance of the monitor is evaluated when a spoofer tracks and estimates the aircraft position. To create the worst case spoofing conditions, we analytically derive a Kalman filter-based worst-case sequence of spoofed GNSS measurements. Utilizing this worst-case spoofing attack scenario during a Boeing 747 (B747) final approach, we prove that unless the spoofer's position-tracking devices have unrealistic accuracy and no-delay, the proposed INS monitor performance is highly effective in detecting spoofing attacks.
ASJC Scopus subject areas
- Control and Systems Engineering
- Mechanical Engineering