AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (6.2 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

A GNSS Anti-Spoofing Technique Based on the Spatial Distribution Characteristic of the Residual Vectors

Department of Electronic Enginnering, Tsinghua University, Beijing 100084, China
Xi’an Modern Control Technology Research Institute, Xi’an 710065, China
Show Author Information

Abstract

Anti-spoofing is becoming a crucial technique for applications with high navigation accuracy and reliability requirements. Anti-spoofing technique based on Receiver Autonomous Integrity Monitoring (RAIM) is a good choice for most Global Navigation Satellite System (GNSS) receivers because it does not require any change to the hardware of the receiver. However, the conventional RAIM method can only detect and mitigate a single spoofing signal. Some improved RAIM methods can deal with more spoofing signals, but the computational complexity increases dramatically when the number of satellites in view increase or need additional information. This paper proposes a new RAIM method, called the SRV-RAIM method, which has a very low computation complexity regardless of the number of satellites in view and can deal with any number of spoofing signals. The key to the new method is the spatial distribution characteristic of the Satellites’ Residual Vectors (SRV). In replay or generative spoofing scenarios, the pseudorange measurements of spoofing signals are consistent, the residual vectors of real satellites and those of spoofing satellites have good separation characteristics in spatial distribution. Based on this characteristic, the SRV-RAIM method is proposed, and the simulation results show that the method can separate the real signals and the spoofing signals with an average probability of 86.55% in the case of 12 visible satellites, regardless of the number of spoofing signals. Compared to the conventional traversal-RAIM method, the performance is only reduced by 3.59%, but the computational cost is reduced by 98.3%, so most of the GNSS receivers can run the SRV-RAIM algorithm in time.

References

[1]
A. Jafarnia-Jahromi, A. Broumandan, J. Nielsen, and G. Lachapelle, Pre-despreading authenticity verification for GPS L1 C/A signals, Navigation, vol. 61, no. 1, pp. 111, 2014.
[2]
Y. Hu, S. Bian, K. Cao, J. Cao, and B. Ji, GNSS spoofing detection based on new signal quality assessment model, GPS Solut., vol. 22, no. 1, p. 28, 2018.
[3]
A. Broumandan, A. Jafarnia-Jahromi, S. Daneshmand, and G. Lachapelle, Effect of tracking parameters on GNSS receivers vulnerability to spoofing attack, in Proc. 29th Int. Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS + 2016), Portland, OR, USA, 2016, pp. 30333043.
[4]
S. Chao, J. W. Cheong, A. G. Dempster, H. Zhao, L. Demicheli, and W. Feng, A new signal quality monitoring method for anti-spoofing, in Proc. China Satellite Navigation Conf., Singapore, 2018. pp. 221231.
[5]
B. M. Ledvina, W. J. Bencze, B. Galusha, and I. Miller, An in-line anti-spoofing device for legacy civil GPS receivers, in Proc. 2010 Int. Technical Meeting of the Institute of Navigation, San Diego, CA, USA, 2010, pp. 698712.
[6]
X. Shang, F. Sun, L. Zhang, J. Cui and Y. Zhang, Detection and mitigation of GNSS spoofing via the pseudorange difference between epochs in a multicorrelator receiver, GPS Solut., vol. 26, no. 2, p. 37, 2022.
[7]
L. He, H. Li, and M. Lu, Dual-antenna GNSS spoofing detection method based on Doppler frequency difference of arrival, GPS Solut., vol. 23, no. 3, p. 78, 2019.
[8]
W. Bai, H. Li, Y. Yang, and M. Lu, Motion state monitoring based GNSS spoofing detection method for repeater spoofing attack, in Proc. 2016 Int. Technical Meeting of the Institute of Navigation, Monterey, CA, USA, 2016, pp. 732738.
[9]
M. Majidi, A. Erfanian, and H. Khaloozadeh, A new approach to estimate true position of unmanned aerial vehicles in an INS/GPS integration system in GPS spoofing attack conditions, Int. J. Automat. Comput., vol. 15, no. 6, pp. 747760, 2018.
[10]
S. Han, D. Luo, W. Meng, and C. Li, Antispoofing RAIM for dual-recursion particle filter of GNSS calculation, IEEE Trans. Aerosp. Electron. Syst., vol. 52, no. 2, pp. 836851, 2016.
[11]
Y. Wei, H. Li, C. Peng, and M. Lu, Time domain differential RAIM method for spoofing detection applications, in Proc. China Satellite Navigation Conf., Singapore, 2019, pp. 606614.
[12]
R. G. Brown, A baseline GPS RAIM scheme and a note on the equivalence of three RAIM methods, Navigation, vol. 39, no. 3, pp. 301316, 1992.
[13]
A. Brown and M. Sturza, The effect of geometry on integrity monitoring performance, in Proc. 46th Annual Meeting of the Institute of Navigation, Atlantic City, NJ, USA, 1990, pp. 121129.
[14]
P. Y. Hwang and R. G. Brown, NIORAIM integrity monitoring performance in simultaneous two-fault satellite scenarios, in Proc. 18th Int. Technical Meeting of the Satellite Division of the Institute of Navigation, Long Beach, CA, USA, 2005, pp. 17601771.
[15]
B. S. Pervan, S. P. Pullen, and J. R. Christie, A multiple hypothesis approach to satellite navigation integrity, Navigation, vol. 45, no. 1, pp. 6171, 1998.
[16]
H. Tao, H. Li, W. Zhang, and M. Lu, A recursive receiver autonomous integrity monitoring (recursive-RAIM) technique for GNSS anti-spoofing, in Proc. 2015 Int. Technical Meeting of the Institute of Navigation, Dana Point, CA, USA, 2015, pp. 738744.
[17]
J. Li, H. Li, C. Peng, J. Wen, and M. Lu, Research on the random traversal RAIM method for anti-spoofing applications, in Proc. China Satellite Navigation Conf., Singapore, 2019, pp. 593605.
[18]
M. A. Sturza and A. K. Brown, Comparison of fixed and variable threshold RAIM algorithms, in Proc. 3rd Int. Technical Meeting of the Satellite Division of the Institute of Navigation, Colorado Spring, CO, USA, 1990, pp. 437443.
[19]
R. G. Brown, G. Y. Chin, and J. H. Kraemer, Update on GPS integrity requirements of the RTCA MOPS, in Proc. 4th Int. Technical Meeting of the Satellite Division of the Institute of Navigation, Albuquerque, NM, USA, 1991, pp. 761772.
Tsinghua Science and Technology
Pages 457-468
Cite this article:
Wu Q, Cui X, Lu M, et al. A GNSS Anti-Spoofing Technique Based on the Spatial Distribution Characteristic of the Residual Vectors. Tsinghua Science and Technology, 2024, 29(2): 457-468. https://doi.org/10.26599/TST.2023.9010017

1293

Views

322

Downloads

0

Crossref

1

Web of Science

1

Scopus

0

CSCD

Altmetrics

Received: 27 October 2022
Revised: 06 March 2023
Accepted: 17 March 2023
Published: 22 September 2023
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

Return