C/N0 Analysis-Based GPS Spoofing Detection with Variable Antenna Orientations

TL;DR

The paper tackles GPS spoofing threats in aviation by proposing a lightweight, receiver-centered method that detects spoofing through $C/N_0$ variation as the antenna orientation changes. By comparing real-sky and spoofed data collected with a u-blox receiver and a GPSG-1000 simulator, it demonstrates distinct orientation-dependent patterns in genuine signals that are absent in spoofed ones. Two detection models—rule-based and geometry-based pattern detection—are developed to identify anomalies without cryptographic or hardware-heavy solutions. The findings suggest that simple attitude maneuvers, or orientation changes, can reveal spoofing signatures, enabling practical, low-cost defenses for general aviation and UAV systems with potential for real-time deployment.

Abstract

GPS spoofing poses a growing threat to aviation by falsifying satellite signals and misleading aircraft navigation systems. This paper demonstrates a proof-of-concept spoofing detection strategy based on analyzing satellite Carrier-to-Noise Density Ratio (C/N$_0$) variation during controlled static antenna orientations. Using a u-blox EVK-M8U receiver and a GPSG-1000 satellite simulator, C/N$_0$ data is collected under three antenna orientations flat, banked right, and banked left) in both real-sky (non-spoofed) and spoofed environments. Our findings reveal that under non-spoofed signals, C/N$_0$ values fluctuate naturally with orientation, reflecting true geometric dependencies. However, spoofed signals demonstrate a distinct pattern: the flat orientation, which directly faces the spoofing antenna, consistently yielded the highest C/N$_0$ values, while both banked orientations showed reduced C/N$_0$ due to misalignment with the spoofing source. These findings suggest that simple maneuvers such as brief banking to induce C/N$_0$ variations can provide early cues of GPS spoofing for general aviation and UAV systems.

Figures (6)

• Figure 1: Spoofing detection experiment setup featuring the patch antenna, red Faraday cage for signal isolation, and GPS simulator on the right.
• Figure 2: Outdoor data collection setup for capturing real-sky (non-spoofed) and spoofed GPS signals under controlled antenna orientations.
• Figure 3: Non-Spoofed (top) vs. Spoofed (bottom) Signal Strengths for three orientations (left-banked, flat, and right-banked).
• Figure 4: Plot showing satellites with increasing signal strength.
• Figure 5: Plot showing satellites with decreasing signal strength.