In GNSS spoofing detection, anomalies are flagged by which criterion when using joint sensor data?

• A. Anomalies flagged by sudden changes in C/N0 only
• B. Anomalies flagged by energy detection threshold
• C. Anomalies flagged by inconsistency across multiple sensors (e.g., INS, stellar sensors, or another GNSS)
• D. Anomalies flagged by parity checks in GNSS

Answer: (C)

Cross-sensor consistency is what reveals spoofing when you fuse multiple sources of navigation data. If GNSS is fed into a system that also uses independent sensors like an INS, stellar sensors, or another GNSS, the fused state estimate relies on agreement among these sources. When spoofing occurs, the GNSS output can look believable on its own, but the independent sensors don’t lie: their estimates will drift apart from the GNSS solution. The fusion filter will produce large residuals or inconsistencies across sensors, triggering the anomaly alert.

That’s why this approach is powerful: it detects a mismatch between spoofed GNSS information and independent measurements, rather than relying on a single GNSS signal characteristic. In contrast, sudden changes in C/N0 or simple energy thresholds can be spoofed or mislead by environmental factors, and parity checks operate within GNSS processing alone, not across multiple sensors.