GNSS Spoofing Detection via the Intersection Angle between Two Directions of Arrival in a Single Rotating Antenna

Chen, Shimiao and Ni, Shuyan and Lei, Tuofeng and Cheng, Lingfeng and Song, Xin (2024) GNSS Spoofing Detection via the Intersection Angle between Two Directions of Arrival in a Single Rotating Antenna. Sensors, 24 (4). p. 1116. ISSN 1424-8220

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Abstract

Spoofing against the Global Navigation Satellite System (GNSS) is an attack with strong concealment, posing a significant threat to the security of the GNSS. Many strategies have been developed to prevent such attacks, but current detection methods based on signal direction for multi-agent spoofing require multiple antennas/receivers, leading to increased cost and complexity in implementation. Additionally, methods utilizing a moving single antenna cannot effectively detect multi-agent spoofing. Therefore, we introduce a novel spoofing-detection technique based on the intersection angle between two directions of arrival (IA-DOA) using a single rotating antenna. The essence of this approach lies in estimating the IA-DOA between a pair of signals by utilizing the carrier-to-noise ratio (CNR) and carrier phase single difference (CPSD) of the received signal. The estimation of IA-DOA should be consistent with the prediction when there is no spoofing. With spoofing, it is difficult to accurately simulate the directionality of navigation signals, which can disrupt the consistency between the estimation and prediction of IA-DOA. Therefore, estimations and predictions of IA-DOA can be used to establish detection variables through generalized likelihood ratio testing (GLRT) to detect multi-agent spoofing. We conducted a simulation to analyze the impact of the antenna’s parameters on the detection performance and evaluated it through on-site experiments. The results indicate that the method proposed in this article can efficiently achieve real-time detection of multi-agent spoofing.

Item Type: Article
Subjects: GO for STM > Multidisciplinary
Depositing User: Unnamed user with email support@goforstm.com
Date Deposited: 09 Feb 2024 06:02
Last Modified: 09 Feb 2024 06:02
URI: http://archive.article4submit.com/id/eprint/2671

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