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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: lihongee@tsinghua.edu.cn)
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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 

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