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A GPS Spoofing Signal Detection Method Based on Low Frequency Power Spectrum

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Abstract

With the gradual enlargement of the application of satellite navigation spoofing signals in the field of anti-drone and other areas, spoofing signals have severely threatened the application of satellite navigation system. As spoofing signals exhibit strong concealment characteristics and difficulties in detection and identification, this study proposed a GPS deception signal detection method based on a low-frequency power spectrum. Data acquisition was achieved using a conventional satellite navigation spoofing signal receiving equipment, and a spoofing signal processing method based on low-frequency power spectrum and Kalman filtering was adopted. The method achieved a spoofing signal detection accuracy reaches 92.8%.

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References

  1. Margaria, D., Motella, B., Anghileri, M., Floch, J., Fernández-Hernández, I., & Paonni, M. (2017). Signal structure-based authentication for civil GNSSs: Recent solutions and perspectives. IEEE Signal Processing Magazine, 34(5), 27–37.

    Article  Google Scholar 

  2. Jafarnia, A., Broumandan, A., Nielsen, J., et al. (2014). Pre-despreading authenticity verification for GPS L1 C/A signals. Navigation, 61(1), 1–11.

    Article  Google Scholar 

  3. Chen, J., Xu, Y., Yuan, H., & Yuan, Y. (2020). A new GNSS spoofing detection method using two antennas. IEEE Access, 8, 110738–110747.

    Article  MATH  Google Scholar 

  4. Guoli, Z. H. A. N. G., Jicheng, D. I. N. G., & Yao, Z. H. A. N. G. (2020). Research on repeater deception jamming detection algorithm based on GNSS signal delay characteristics. Radio Engineering, 49(7), 626–630.

    MATH  Google Scholar 

  5. Dehghanian, Vahid, Nielsen, John, Lachapelle, Gerard, et al. (2012). GNSS spoofing detection based on receiver C/N0 estimates. ION GNSS2012, 4, 2875–2884.

    MATH  Google Scholar 

  6. Wesson, K. D., Evans, B. L., & Humphreys, T. E. (2013). A combined symmetric difference and power monitoring GNSS anti-spoofing technique[C]. 2013 IEEE Global Conference on Signal and Information Processing. pp.217-220, 2013.

  7. Li, J., Zhang, J., Chang, S., & Zhou, M. (2016). Performance evaluation of multimodal detection method for GNSS intermediate spoofing. IEEE Access, 4, 9459–9468.

    Article  MATH  Google Scholar 

  8. Sun, C., Cheong, J. W., Dempster, A. G., Zhao, H., & Feng, W. (2018). GNSS spoofing detection by means of signal quality monitoring (SQM) metric combinations. IEEE Access, 6, 66428–66441.

    Article  Google Scholar 

  9. Baziar, A. R., Mosavi, M. R., & Moazedi, M. (2019). Spoofing mitigation using double stationary wavelet transform in civil GPS receivers. Wireless Personal Communications, 109(3), 1827–1844.

    Article  Google Scholar 

  10. Shuli, D., Taotao, Z., & Min, L. A. (2019). GNSS Anti-Spoofing Technology Based on Power Detection[C]. 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC). pp.1134-1137, May.

  11. Schmidt, E., Gatsis, N., & Akopian, D. (2020). A GPS spoofing detection and classification correlator-based technique using the LASSO. IEEE Transactions on Aerospace and Electronic Systems, 56(6), 4224–4237.

    Article  MATH  Google Scholar 

  12. Shafiee, E., Mosavi, M. R., & Moazedi, M. (2021). A modified imperialist competitive algorithm for spoofing attack detection in single-frequency GPS receivers. Wireless Personal Communications, 119, 919–940.

    Article  Google Scholar 

  13. Wang, L., & Zhang, L. J. (2022). Wu, R.B. GNSS spoofing detection based on power monitoring combined with SQM. Journal of Signaling Process. 1-12.

  14. Yang, H., ** R., Xu, W., Che, L., & Zhen, W. (2023). Satellite Navigation Spoofing Interference Detection and Direction Finding Based on Array Antenna. Sensors,23(3), 1604.

  15. Wu, Z., Zhang, Y., Yang, Y., Liang, C., & Liu, R. (2020). Spoofing and anti-spoofing technologies of global navigation satellite system: A survey. IEEE Access, 1-1.

  16. Chunlian, An., Guyue, Yang, & Yanju, Yang. (2021). Direction finding method for strong impact noise background based on median filter preprocessing. Chinese Journal of Electronics, 49(6), 1159–1166.

    MATH  Google Scholar 

  17. Chunlin, L. I., & Yong, W. U. (2011). Fast power spectrum estimation method based on FFT and autocorrelation function. Ship Electronic Engineering., 31, 92–95.

    MATH  Google Scholar 

  18. Ananthi, G. (2023). State of charge estimation in electric vehicles using improved strong tracking Kalman filter algorithm. Wireless Personal Communications, 128(1), 147–160.

    Article  MATH  Google Scholar 

  19. Zhong, Y. U., Yichao, H. U. A. N. G., & Chang, G. U. O. (2021). Application of Kalman filter combined with neural network in MEMS sensors. Transducer and Microsystem Technologies, 40(11), 154–156+160.

    MATH  Google Scholar 

  20. Fan, Guangteng, Ran, Dechao, Zhang, Fei, & Tuo, Zhouhui. (2020). Mobile terminal spoofing detection method based on power variation. GNSS World of China, 45(11), 66–70.

    MATH  Google Scholar 

  21. Tang, Ping, Wang, Shuai, Li, Xiangming, & Jiang, Zhike. (2017). A low-complexity algorithm for fast acquisition of weak DSSS signal in high dynamic environment. GPS Solutions, 21(4), 1427–1441.

    Article  MATH  Google Scholar 

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Correspondence to Jiancun Zuo.

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Li, G., Peng, Y., Ma, J. et al. A GPS Spoofing Signal Detection Method Based on Low Frequency Power Spectrum. Wireless Pers Commun 139, 1783–1795 (2024). https://doi.org/10.1007/s11277-024-11697-w

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