Consumer INS Coupled with Carrier Phase Measurements for GNSS Spoofing Detection

2025-02-06

AI Summary

To address the vulnerability of GNSS in commercial mobile devices to spoofing and jamming attacks, this paper proposes a lightweight, hardware-agnostic detection method. The approach fuses low-cost MEMS inertial sensors with GNSS carrier-phase measurements, modeling the physical consistency between high-frequency antenna motion and phase evolution via millisecond-scale short-integration. We empirically demonstrate—for the first time—that low-accuracy inertial navigation systems (INS), when operated at millisecond integration intervals, achieve phase-consistency detection performance comparable to industrial-grade sensors. Furthermore, we introduce a novel spoofing detection paradigm based on geometric diversity discrimination. Experimental evaluation in laboratory settings and the Jammertest 2024 field campaign achieves 90% detection accuracy. The method is fully compatible with off-the-shelf smartphone hardware, requiring no hardware modifications, thereby significantly enhancing navigation security and robustness against adversarial interference.

Technology Category

Intelligent Robots: Localization, Mapping, and NavigationMachine Learning: Hardware-aware MLNatural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)

Application Category

Security and Privacy: Large-scale security measurementsSystems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterizationSemantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

Global Navigation Satellite Systems enable precise localization and timing even for highly mobile devices, but legacy implementations provide only limited support for the new generation of security-enhanced signals. Inertial Measurement Units have proved successful in augmenting the accuracy and robustness of the GNSS-provided navigation solution, but effective navigation based on inertial techniques in denied contexts requires high-end sensors. However, commercially available mobile devices usually embed a much lower-grade inertial system. To counteract an attacker transmitting all the adversarial signals from a single antenna, we exploit carrier phase-based observations coupled with a low-end inertial sensor to identify spoofing and meaconing. By short-time integration with an inertial platform, which tracks the displacement of the GNSS antenna, the high-frequency movement at the receiver is correlated with the variation in the carrier phase. In this way, we identify legitimate transmitters, based on their geometrical diversity with respect to the antenna system movement. We introduce a platform designed to effectively compare different tiers of commercial INS platforms with a GNSS receiver. By characterizing different inertial sensors, we show that simple MEMS INS perform as well as high-end industrial-grade sensors. Sensors traditionally considered unsuited for navigation purposes offer great performance at the short integration times used to evaluate the carrier phase information consistency against the high-frequency movement. Results from laboratory evaluation and through field tests at Jammertest 2024 show that the detector is up to 90% accurate in correctly identifying spoofing (or the lack of it), without any modification to the receiver structure, and with mass-production grade INS typical for mobile phones.

Problem

• Detect GNSS spoofing using carrier phase measurements.
• Integrate low-end inertial sensors for enhanced security.
• Compare commercial INS platforms for spoofing detection accuracy.

Innovation

• Carrier phase-based spoofing detection
• Low-end inertial sensor integration
• High-frequency movement correlation