GPS Spoofing Mitigation using Adaptive Estimator in Tracking Loop

Document Type : Original Article

Authors

Abstract

The attacks such as spoofing is one of the main sources of error in tracking of Global Positioning System (GPS) receivers. The aim of these attacks is to calculate fake time and position. The spoofer sends the counterfeit signal and causes to spoof. This counterfeit signal is generated in different ways. In this paper, the studied interference is the delay spoof. Indeed, the aim is introducing a new approach in tracking loop of the GPS receiver in order to decrease the generated delay by spoof attack. The suggested algorithm has two main steps. The first step estimates the amount of delay spoof. Subsequently, through an innovative approach, the effect of spoofing signal is extracted and then subtracted from the total measured correlation function. To achieve that, the effect of spoofing signal is estimated and the estimated spoofing signal is generated separately. For this purpose, two estimator based on multi-correlator and adaptive approach is introduced. Correlation of this signal with the digital IF signal is calculated and entered into the spoof mitigation part. In this part, correlation of this signal is added to auto-correlation of received signal and correlation of authentic signal is achieved. These techniques provide easy-to-implement and quality assurance tools for anti-spoofing. Applying the proposed algorithm decreases the average spoofing error by 88%.

Keywords


[1]     A. Broumandan, A. Jafarnia-Jahromi, and G. Lachapelle, “Spoofing Detection, Classification and Cancelation (SDCC) Receiver Architecture for a Moving GNSS Receiver,” GPS Solution, vol. 19, pp. 475-487, 2015.‎
[2]     A. R. Baziar, M. Moazedi, and M. R. Mosavi, “Analysis of Single Frequency GPS Receiver under Delay and Combining Spoofing Algorithm,” Wireless Personal Communications, vol. 83, no. 3, pp. 1955-1970, 2015.
[3]     M. R. Mosavi, and Z. Shokhmzan, “Spoofing Mitigation of GPS Receivers using Normalized Least Mean Squares,” Iranian Journal of Electrical and Electronic Engineering, vol.11, no.3, pp. 1-11, 2015.
[4]     C. Bonebrake and L. R. O''''''''Neil, “Attacks on GPS Time Reliability,” IEEE Transactions on Security & Privacy, vol. 12, no. 3, pp. 82-85, June 2014.
[5]     N. Shafiee, M. R. Mosavi, and M. Moazedi, “Detection of Delay Spoofing Attack base on Multi-Layer Neural Network in Single-Frequency GPS Receiver,” Journal of Electronics and Cyber Defense, vol.3, no.1, pp. 69-80,  2015. (in Persian)
[6]     Z. Shokhmzan and M. R. Mosavi, “Defense Against Spoofing in GPS Receiver using Correlation and Least Mean Squares Method Based on Sign-Data Algorithm,” Journal of Electronics and Cyber Defense, vol. 3, no. 4, pp. 11-22, 2016. (in Persian)
[7]     M. R. Mosavi, M. J. Rezaei, N. Hosseinzadeh,                                    and R. A. Kiaamiri, “New Intelligent Methods for Detection and Mitigation of Spoofing Signal in GPS Receivers,” Journal of Electronics and Cyber Defense, vol. 2, no.1, pp. 71-81, 2014. (in Persian)
[8]     M. R. Mosavi and F. Shafiee, “Narrowband Interference Suppression for GPS Navigation using Neural Networks,” Journal of GPS Solutions, vol. 20, no. 3, pp. 341-351, 2016.
 
 
 
 
 
[9]     K. C. Kwon, C. K. Yang and D. S. Shim, “Spoofing Signal Detection using Accelerometers in IMU and GPS Information,” The Transactions of the Korean Institute of Electrical Engineers, vol. 63, no. 9, pp. 1273-1280, Sep. 2014.
[10]  A. Farhadi, M. Moazedi, M. R. Mosavi, and A. Sadr, “A Novel Ratio-Phase Metric of Signal Quality Monitoring for Real-Time Detection of GPS Interference,” Journal of Wireless Personal Communications, 2017.
[11]  A. Javaid, F. Jahan, and W. Sun, “Analysis of Global Positioning System-based Attacks and a Novel Global Positioning System Spoofing Detection/Mitigation Algorithm for Unmanned Aerial Vehicle Simulation,” Simulation: Transactions of the Society for Modeling and Simulation International, vol. 93, no. 5, pp. 427-441, 2017.
[12]  J. Nielsen, A. Broumandan, and G. Lachapelle, “Spoofing Detection and Mitigation with a Moving Handheld Receiver,” GPS World Magazine, vol. 21, no. 9, pp. 27-33, Sep. 2010.
[13]  S. Daneshmand, “GNSS Interference Mitigation using Antenna Array Processing,” Ph.D. Thesis, Department of Geometrics Engineering, University of Calgary, Alberta, April 2013.
[14]  J. Nielsen, A. Broumandan, and G. Lachapelle, “GNSS Spoofing Detection for Single Antenna Handheld Receivers,” Journal of the Institute of Navigation, vol. 58, no. 4, pp.       335-344, Sep.2011.
[15]  J. Magiera and R. Katulski, “Detection and Mitigation of GPS Spoofing Based on Antenna Array Processing,” Journal of Applied Research and Technology, vol. 13, pp. 45-57, 2015.
[16]  D. P. Shepard and T. E. Humphreys, “Characterization of Receiver Response to Spoofing Attacks,” GPS World, vol. 21, no. 9, pp. 27-33, 2010.
[17]  Y. Yang and J. Xu, “GNSS Receiver Autonomous Integrity Monitoring (RAIM) Algorithm based on Robust Estimation,” Geodesy and Geodynamics, vol. 7, no. 2, pp. 117-123, March 2016.
[18]  D. J. Jwo and Z. M. Wen, “Neural Network Assisted Vector Tracking Loop for Bridging GPS Signal Outages,”  Applied Mechanics and Materials, vols. 764-765, pp. 560-564, 2015.
[19]  L. Baoa, R. Wub, W. Wangb, and D. Lub, “Spoofing Mitigation in Global Positioning System Based on C/A Code Self-coherence with Array Signal Processing,” Journal of Communications Technology and Electronics, vol. 62, no. 1, pp. 66-73, 2017.
[20]  A. Cavaleri, B. Motella, M. Pini, and M. Fantino, “Detection of Spoofed GPS Signals at Code and Carrier Tracking Level,” The 5th ESA Workshop on Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing, pp. 1-6, Dec. 2010.
[21]  J. Huanga, L. L. Prestia, B. Motella, and M. Pini, “GNSS Spoofing Detection: Theoretical Analysis and Performance of the Ratio Test Metric in Open Sky,” vol. 2, pp. 37-40, 2016.
[22]  C. L. Chang and J. C. Juang, “An Adaptive Multipath Mitigation Filter for GNSS Application,” CACS Automatic Control Conference, pp. 1-6, Nov. 2005.
[23]  X. Fan, Li. Du, and D. Duan, “Synchrophasor Data Correction under GPS Spoofing Attack: A State Estimation based Approach,” IEEE Transactions on Smart Grid, pp. 1-11, 2017.
[24]  E. Shafiee, M. R. Mosavi, and M. Moazedi, “Detection of Spoofing Attack using Machine Learning based on            Multi-Layer Neural Network in Single-Frequency GPS Receivers,” Journal of Navigation, pp. 1-20, 2017.
Volume 6, Issue 3 - Serial Number 23
November 2018
Pages 65-80
  • Receive Date: 18 December 2017
  • Revise Date: 09 May 2018
  • Accept Date: 27 May 2018
  • Publish Date: 22 November 2018