Abstract: | Global Navigation Satellite System (GNSS) spoofing attack, a serious threat to GNSS services across various sectors, occurs intermittently. Receiver Power Monitoring (RPM) is an effective algorithm to detect such attack by taking into account both AGC and C/N0 fluctuations. However, RPM has two notable limitations: it is primarily effective only during the initial stage of overpowered spoofing attack, and establishing an effective detection threshold proves challenging. In this study, we propose improvements to RPM by introducing 4 types of data features: carrier-to-noise ratio (C/N0) correlation coefficients, C/N0 fluctuations and their first-order differences, the number of visible satellites and satellites used for positioning within each constellation/frequency band, and the percentage of nulls in the sliding window of AGC and C/N0. The Random Forest (RF) algorithm was employed as the foundation for a data-driven approach to train an anti-spoofing detection model. To evaluate the performance of the improved algorithm, we collected AGC and C/N0 data from both authentic and spoofing signals under varying motion states at 4 representative sites. The extracted data features were used to build a detection model utilizing the RF algorithm. The model evaluation results demonstrate that the RF-RPM algorithm effectively addresses more complex spoofing scenarios, with an out-of-bag (OOB) error rate of less than 1.64% when the decision tree size exceeds 15. This study lays the groundwork for future engineering implementations and scientific research in GNSS anti-spoofing field. |
Published in: |
Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024) September 16 - 20, 2024 Hilton Baltimore Inner Harbor Baltimore, Maryland |
Pages: | 1311 - 1319 |
Cite this article: | He, Min, Li, Hong, Wang, Hao, Wu, Zhenyang, Wang, Lintao, Lu, Mingquan, "Potential Problem Analysis and RF Based Improvement of RPM on Android Devices," Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024), Baltimore, Maryland, September 2024, pp. 1311-1319. https://doi.org/10.33012/2024.19732 |
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