Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-03T02:17:51.216Z Has data issue: false hasContentIssue false
  • English
  • Français

Statistical Model and Performance Evaluation of a GNSS Spoofing Detection Method based on the Consistency of Doppler and Pseudorange Positioning Results

Published online by Cambridge University Press:  25 October 2018

Fengkui Chu ,
Hong Li ,
Jian Wen Open the ORCID record for Jian Wen [Opens in a new window]  and
Mingquan Lu
Fengkui Chu
Affiliation:
(Department of Electronic Engineering, Tsinghua University, Beijing 100084, China)
Hong Li*
Affiliation:
(Department of Electronic Engineering, Tsinghua University, Beijing 100084, China)
Jian Wen
Affiliation:
(Department of Electronic Engineering, Tsinghua University, Beijing 100084, China)
Mingquan Lu
Affiliation:
(Department of Electronic Engineering, Tsinghua University, Beijing 100084, China)
*
(E-mail: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Global Navigation Satellite System (GNSS) safety issues of have been of concern for some time. Spoofing attacks have received much attention as they can be difficult to detect and have the potential to cause disruption at best and major damage in extremis. To mitigate such threats, a spoofing detection method based on the consistency check of Doppler positioning fixes and pseudorange positioning fixes is proposed. The primary contributions of this paper include establishing a Generalised Likelihood Ratio Test (GLRT)-based statistical detection model for the introduced spoofing detection method and efficiently improving the accuracy of the Doppler positioning method as well as the performance of the detection approach by a modified α-filter-based Doppler smoothing technique. Theoretical performance of the proposed detection model is analysed. Monte Carlo simulations were also conducted to verify the theoretical analysis. Moreover, grounded on the developed test statistic and the optimised threshold, a consistency check module was specifically realised in both software defined and real-time GNSS receivers. Additionally, a Doppler smoothing technique was applied to the receivers. Spoofing attack experiments on both software defined and real-time platforms validated the effectiveness of the statistical spoofing detection model.

Keywords

GNSSAnti-spoofingDopplerModelling
Type
Research Article
Information
The Journal of Navigation , Volume 72 , Issue 2 , March 2019 , pp. 447 - 466
Copyright
Copyright © The Royal Institute of Navigation 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Cetin, E., Thompson, R. J. R. and Dempster, A. G. (2014). Passive Interference Localization within the GNSS Environmental Monitoring System (GEMS): TDOA Aspects. GPS Solutions, 18, 483–495.Google Scholar
Chen, H. W., Wang, H. S., Chiang, Y. T. and Chang, F. R. (2014). A New Coarse-Time GPS Positioning Algorithm Using Combined Doppler and Code-Phase Measurements. GPS Solutions, 18, 541–551.Google Scholar
Chu, F., Li, H., Wen, J., Wu, H. and Lu, M. (2017). An Anti-Spoofing Method Based on Doppler Positioning. Proceedings of the 2017 International Technical Meeting of The Institute-of-Navigation, Monterey, CA.Google Scholar
Guier, W. H. and Weiffenbach, G. C. (1960). A Satellite Doppler Navigation System. Proceedings of the Institute of Radio Engineers, 48, 507–516.Google Scholar
Humphreys, T. E., Ledvina, B. M., Psiaki, M. L., O'Hanlon, B. W. and Kintner, P. M. Jr. (2008). Assessing the Spoofing Threat: Development of a Portable GPS Civilian Spoofer. Proceedings of the 21st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2008), Savannah, GA.Google Scholar
Jafarnia-Jahromi, A., Broumandan, A., Nielsen, J. and Lachapelle, G. (2012). GPS Vulnerability to Spoofing Threats and a Review of Antispoofing Techniques. International Journal of Navigation and Observation, 2012, 16 pages.Google Scholar
Jing, S. R., Xu, B., Yong, L. and Sun, G. F. (2015). Doppler-Aided Rapid Positioning Method for BDS Receivers. Electronics Letters, 51, 2139–2141.Google Scholar
Jones, M. (2017). Spoofing in the Black Sea: What really happened? http://gpsworld.com/spoofing-in-the-black-sea-what-really-happened/. GPS World, Accessed 11 October 2017.Google Scholar
Kay, S. M. (1998). Fundamentals of Statistical Signal Processing Volume II: Detection Theory. Prentice Hall.Google Scholar
Lehtinen, A. (2002). Doppler Positioning with GPS. M. A. Sc. Thesis, Tampere University of Technology, Tampere, Finland.Google Scholar
Li, L., Zhong, J. and Zhao, M. (2011). Doppler-Aided GNSS Position Estimation with Weighted Least Squares. IEEE Transactions on Vehicular Technology, 60, 3615–3624.Google Scholar
Othieno, N. (2012). Combined Doppler and Time-Free Navigation for Low Dynamics Receivers. M. A. Sc. Thesis, Concordia University, Montreal, Canada.Google Scholar
Psiaki, M. L. and Humphreys, T. E. (2016a). Attackers Can Spoof Navigation Signals Without Our Knowledge. Here's How to Fight Back GPS Lies. IEEE Spectrum, 53, 26–53.Google Scholar
Psiaki, M. L. and Humphreys, T. E. (2016b). GNSS Spoofing and Detection. Proceedings of the IEEE, 104, 1258–1270.Google Scholar
Simon, M. K. (2006). Probability Distributions Involving Gaussian Random Variables. Springer.Google Scholar
Wang, Q. and Xu, T. (2011). Combining GPS Carrier Phase and Doppler Observations for Precise Velocity Determination. Science China-Physics Mechanics & Astronomy, 54, 1022–1028.Google Scholar
Warner, J. S. and Johnson, R. G. (2002). A Simple Demonstration That the Global Positioning System (GPS) is Vulnerable to Spoofing. Journal of Security Administration, 25, 19–27.Google Scholar