• Vehicular autonomous mobility is tackled at the individual or at the system level: self-driving cars (ADAS) versus intelligent transport systems (ITS)
• Self-driving cars seek to replicate human drivers
• ADAS Level 2 installed in multi-million vehicles
• ADAS Level 3/4 approved  for on-demand cab service, uses a mix of sensors including camera, lidar, radar, GNSS, odometry, etc.
• ITS seeks to solve the autonomy puzzle from the system level: significantly less funding, mostly restricted to pilot programs
• GNSS plays major role in the autonomy stack in spite of its significant advantages  of absolute positioning, weather-agnostic, low computational need

• Spoofing includes retransmission of authentic GNSS signals, code/carrier attack, navigation data attack,
• Anti-spoofing solutions include signal processing, cryptographic, and antenna-level defense
• Signal processing defense detects anomalies in the signal power and lack of consistency between different bands and constellations using multi-band multi-constellation set-up
• Cryptographic defense: signal authentication using authentication codes
• Antenna level: Angle of Arrival (AoA) defense w/ antenna arrays
• Signal processing defense incorporated in leading automotive receivers
• Cryptographic  defense: OSNMA launched, incorporation in receivers expected in the coming years
• Antenna level: at R&D/early productization phase, not incorporated in commercially available products

Integration and Validation

Following component-level qualification, the integrated SCS-GNSS-1 system underwent comprehensive verification testing:

• Laboratory Tests: Simulated spoofing attacks validated the system’s ability to detect signal anomalies. Directional accuracy and detection latency were assessed using phase-shifted GNSS signal inputs.
• Field Tests: Real GNSS signals and live spoofing devices (e.g., HackRF One with Portapack) were employed to evaluate system performance under operational conditions.

Verification confirmed the system’s compliance with key requirements, though opportunities for optimization were identified, particularly regarding detection latency and user alerting mechanisms.

Field Validation and Results

Field validation trials were conducted across diverse environments:

Rural/Open Field Environments

In low-reflection environments, the system demonstrated robust detection capabilities, reliably identifying spoofing attempts with minimal false alarms.

Suburban Areas

Moderate multipath interference was encountered, but detection performance remained within targeted thresholds.

Urban Canyons

High multipath interference posed challenges, yet the system successfully detected spoofing attempts in most cases. The use of a directional spoofer antenna and signal booster proved critical in achieving adequate test coverage.

Over 400 individual test cases were executed to statistically validate system performance. The prototype met or exceeded target metrics in over 90% of scenarios.

URBAN

Project Cybersecure GNSS Receiver for Autonomous Navigation  (CECIL) was supported by the NAVISP program by ESA