NDLI: Prediction-discrepancy based on innovative particle filter for estimating UAV true position in the presence of the GPS spoofing attacks

Content Provider	IET Digital Library
Author	Majidi, Mohammad Erfanian, Alireza Khaloozadeh, Hamid
Abstract	In this paper, a novel prediction-discrepancy based on innovative particle filter (PDIPF) is proposed to solve the unmanned aerial vehicle (UAV) positioning problem in the presence of the global positioning system (GPS) spoofing attack, supposing that the GPS spoofing effects are in the form of unknown but bounded errors. To cope with the GPS spoofing attacks as unknown sudden changes of system state variables, the compensation of the GPS spoofing effects is adaptively done in two basic parts of PDIPF algorithm including particle weighting and covariance matrix adaption. In addition, a theorem is developed which verifies that the output estimation error is upper bounded by a given probability with the help of the adapted covariance matrix. Besides, the particle weight calculation in PDIPF is done with respect to the prediction discrepancy of generated particles from the GPS measurements. The proposed PDIPF is used to decrease the effects of any GPS spoofing errors with different probability density functions and estimate true position of UAV in the presence of the GPS spoofing attacks. The algorithm is applied to the inertial navigation system/GPS/Loran-C integration systems. Simulation results demonstrate the effectiveness of the proposed PDIPF algorithm in terms of accuracy and redundancy.
Starting Page	887
Ending Page	897
Page Count	11
ISSN	17518784
Volume Number	14
e-ISSN	17518792
Issue Number	Issue 6, Jun (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/14/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2019.0520
Journal	IET Radar, Sonar & Navigation
Publisher Date	2020-02-12
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adapted Covariance Matrix Aerospace Control Autonomous Aerial Vehicle Covariance Matrices Covariance Matrix Adaption Filtering Method in Signal Processing Generated Particle Global Positioning System Global Positioning System Spoofing Attack GPS Measurement GPS Spoofing Attack GPS Spoofing Effect Inertial Navigation System Innovative Particle Filter Mobile Robots Novel Prediction-discrepancy Optimisation Technique Output Estimation Error Particle Filter Particle Weight Calculation PDIPF Prediction Discrepancy Probability Radio Navigation And Direction Finding Radionavigation Remotely Operated Vehicle Statistics UAV True Position Unknown But Bounded Error Unmanned Aerial Vehicle Positioning Problem
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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