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GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation
Spoofing attacks are threatening the global navigation satellite system (GNSS). The maximum likelihood estimation (MLE)-based positioning technique is a direct positioning method originally developed for multipath rejection and weak signal processing. We find this method also has a potential ability...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5539650/ https://www.ncbi.nlm.nih.gov/pubmed/28665318 http://dx.doi.org/10.3390/s17071532 |
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author | Wang, Fei Li, Hong Lu, Mingquan |
author_facet | Wang, Fei Li, Hong Lu, Mingquan |
author_sort | Wang, Fei |
collection | PubMed |
description | Spoofing attacks are threatening the global navigation satellite system (GNSS). The maximum likelihood estimation (MLE)-based positioning technique is a direct positioning method originally developed for multipath rejection and weak signal processing. We find this method also has a potential ability for GNSS anti-spoofing since a spoofing attack that misleads the positioning and timing result will cause distortion to the MLE cost function. Based on the method, an estimation-cancellation approach is presented to detect spoofing attacks and recover the navigation solution. A statistic is derived for spoofing detection with the principle of the generalized likelihood ratio test (GLRT). Then, the MLE cost function is decomposed to further validate whether the navigation solution obtained by MLE-based positioning is formed by consistent signals. Both formulae and simulations are provided to evaluate the anti-spoofing performance. Experiments with recordings in real GNSS spoofing scenarios are also performed to validate the practicability of the approach. Results show that the method works even when the code phase differences between the spoofing and authentic signals are much less than one code chip, which can improve the availability of GNSS service greatly under spoofing attacks. |
format | Online Article Text |
id | pubmed-5539650 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-55396502017-08-11 GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation Wang, Fei Li, Hong Lu, Mingquan Sensors (Basel) Article Spoofing attacks are threatening the global navigation satellite system (GNSS). The maximum likelihood estimation (MLE)-based positioning technique is a direct positioning method originally developed for multipath rejection and weak signal processing. We find this method also has a potential ability for GNSS anti-spoofing since a spoofing attack that misleads the positioning and timing result will cause distortion to the MLE cost function. Based on the method, an estimation-cancellation approach is presented to detect spoofing attacks and recover the navigation solution. A statistic is derived for spoofing detection with the principle of the generalized likelihood ratio test (GLRT). Then, the MLE cost function is decomposed to further validate whether the navigation solution obtained by MLE-based positioning is formed by consistent signals. Both formulae and simulations are provided to evaluate the anti-spoofing performance. Experiments with recordings in real GNSS spoofing scenarios are also performed to validate the practicability of the approach. Results show that the method works even when the code phase differences between the spoofing and authentic signals are much less than one code chip, which can improve the availability of GNSS service greatly under spoofing attacks. MDPI 2017-06-30 /pmc/articles/PMC5539650/ /pubmed/28665318 http://dx.doi.org/10.3390/s17071532 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Fei Li, Hong Lu, Mingquan GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation |
title | GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation |
title_full | GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation |
title_fullStr | GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation |
title_full_unstemmed | GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation |
title_short | GNSS Spoofing Detection and Mitigation Based on Maximum Likelihood Estimation |
title_sort | gnss spoofing detection and mitigation based on maximum likelihood estimation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5539650/ https://www.ncbi.nlm.nih.gov/pubmed/28665318 http://dx.doi.org/10.3390/s17071532 |
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