Navigation in GPS Spoofed Environment Using M-Best Positioning Algorithm and Data Association

Intentionally misguiding a global positioning system (GPS) receiver has become a potential threat to almost all civilian GPS receivers in recent years. GPS spoofing is among the types of intentional interference, in which a spoofing device transmits spoofed signals towards the GPS receiver to alter...

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Main Authors: Bethi Pardhasaradhi, Pathipati Srihari, P. Aparna
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9371742/
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author Bethi Pardhasaradhi
Pathipati Srihari
P. Aparna
author_facet Bethi Pardhasaradhi
Pathipati Srihari
P. Aparna
author_sort Bethi Pardhasaradhi
collection DOAJ
description Intentionally misguiding a global positioning system (GPS) receiver has become a potential threat to almost all civilian GPS receivers in recent years. GPS spoofing is among the types of intentional interference, in which a spoofing device transmits spoofed signals towards the GPS receiver to alter the GPS positioning information. This paper presents a robust positioning algorithm, followed by a track filter, to mitigate the effects of spoofing. It is proposed to accept the authentic GPS signals and spoofed GPS signals into the positioning algorithm and perform the robust positioning with all possible combinations of authentic and spoofed pseudorange measurements. The pseudorange positioning algorithm is accomplished using an iterative least squares (ILS). Further, to efficiently represent the robust algorithm, the M-best position algorithm is proposed, in which a likelihood-based cost function optimizes the positions and only provides M-best positions at a given epoch. However, during robust positioning, the positions evolved due to spoofed pseudorange measurements are removed to overcome GPS spoofing. In order to remove the fake positions being evolved owing to wrong measurement associations in the ILS, a gating technique is applied within the Kalman filter (KF) framework. The navigation filter is a three-dimensional KF with a constant velocity (CV) model, all the position estimates evolved at a specific epoch are observations. Besides, to enhance this technique’s performance, the track to position association is performed by using two data association algorithms: nearest neighbor (NN) and probabilistic data association (PDA). Simulations are carried out for GPS receiver positioning by injecting different combinations of spoofed signals into the receiver. The proposed algorithm’s efficiency is given by a success rate metric (defined as the navigation track to follow the true trajectory rather than spoofing trajectory) and position root mean square error (PRMSE).
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spelling doaj.art-75b69eb9742247fcaff566ad030110b52022-12-21T23:07:20ZengIEEEIEEE Access2169-35362021-01-019515365154910.1109/ACCESS.2021.30643839371742Navigation in GPS Spoofed Environment Using M-Best Positioning Algorithm and Data AssociationBethi Pardhasaradhi0Pathipati Srihari1https://orcid.org/0000-0001-9168-2753P. Aparna2Electronics and Communication Department, National Institute of Technology Karnataka, Surathkal, Surathkal, IndiaElectronics and Communication Department, National Institute of Technology Karnataka, Surathkal, Surathkal, IndiaElectronics and Communication Department, National Institute of Technology Karnataka, Surathkal, Surathkal, IndiaIntentionally misguiding a global positioning system (GPS) receiver has become a potential threat to almost all civilian GPS receivers in recent years. GPS spoofing is among the types of intentional interference, in which a spoofing device transmits spoofed signals towards the GPS receiver to alter the GPS positioning information. This paper presents a robust positioning algorithm, followed by a track filter, to mitigate the effects of spoofing. It is proposed to accept the authentic GPS signals and spoofed GPS signals into the positioning algorithm and perform the robust positioning with all possible combinations of authentic and spoofed pseudorange measurements. The pseudorange positioning algorithm is accomplished using an iterative least squares (ILS). Further, to efficiently represent the robust algorithm, the M-best position algorithm is proposed, in which a likelihood-based cost function optimizes the positions and only provides M-best positions at a given epoch. However, during robust positioning, the positions evolved due to spoofed pseudorange measurements are removed to overcome GPS spoofing. In order to remove the fake positions being evolved owing to wrong measurement associations in the ILS, a gating technique is applied within the Kalman filter (KF) framework. The navigation filter is a three-dimensional KF with a constant velocity (CV) model, all the position estimates evolved at a specific epoch are observations. Besides, to enhance this technique’s performance, the track to position association is performed by using two data association algorithms: nearest neighbor (NN) and probabilistic data association (PDA). Simulations are carried out for GPS receiver positioning by injecting different combinations of spoofed signals into the receiver. The proposed algorithm’s efficiency is given by a success rate metric (defined as the navigation track to follow the true trajectory rather than spoofing trajectory) and position root mean square error (PRMSE).https://ieeexplore.ieee.org/document/9371742/Anti-spoofingdata associationGPS spoofingM-best positioningnavigation filterrobust positioning
spellingShingle Bethi Pardhasaradhi
Pathipati Srihari
P. Aparna
Navigation in GPS Spoofed Environment Using M-Best Positioning Algorithm and Data Association
IEEE Access
Anti-spoofing
data association
GPS spoofing
M-best positioning
navigation filter
robust positioning
title Navigation in GPS Spoofed Environment Using M-Best Positioning Algorithm and Data Association
title_full Navigation in GPS Spoofed Environment Using M-Best Positioning Algorithm and Data Association
title_fullStr Navigation in GPS Spoofed Environment Using M-Best Positioning Algorithm and Data Association
title_full_unstemmed Navigation in GPS Spoofed Environment Using M-Best Positioning Algorithm and Data Association
title_short Navigation in GPS Spoofed Environment Using M-Best Positioning Algorithm and Data Association
title_sort navigation in gps spoofed environment using m best positioning algorithm and data association
topic Anti-spoofing
data association
GPS spoofing
M-best positioning
navigation filter
robust positioning
url https://ieeexplore.ieee.org/document/9371742/
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