A Foundational Framework for an UAV GPS Jamming Simulator

This paper presents a theoretical framework for a GPS signals jamming simulator designed to evaluate the effects of jamming on a GPS receiver onboard a UAV in an aerodynamic environment. This methodological study focuses on modeling the jammer, the GPS receiver, the propagation environment, and the electronic attack scenario. While commercially available GNSS jamming simulators exist, they can be expensive due to their complexity. This proposed simulator offers an alternative approach to assess the reliability of GPS observables like pseudo ranges, carrier phases, and Doppler measurements under jamming attacks. Furthermore, the framework allows for the exploration and development of anti-jamming techniques capable of detection, mitigation, and localization of interference sources.

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Publication Details

Published
2024-10-17
DOI
https://doi.org/10.1109/icoa62581.2024.10754331
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
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article

A Foundational Framework for an UAV GPS Jamming Simulator

Ismail Lagrat, Issam Senhaji-Mouhaddib, Samir Bouzakri
Robotic Path Planning Algorithms
article

A Foundational Framework for an UAV GPS Jamming Simulator

Ismail Lagrat, Issam Senhaji-Mouhaddib, Samir Bouzakri
article en

Abstract

This paper presents a theoretical framework for a GPS signals jamming simulator designed to evaluate the effects of jamming on a GPS receiver onboard a UAV in an aerodynamic environment. This methodological study focuses on modeling the jammer, the GPS receiver, the propagation environment, and the electronic attack scenario. While commercially available GNSS jamming simulators exist, they can be expensive due to their complexity. This proposed simulator offers an alternative approach to assess the reliability of GPS observables like pseudo ranges, carrier phases, and Doppler measurements under jamming attacks. Furthermore, the framework allows for the exploration and development of anti-jamming techniques capable of detection, mitigation, and localization of interference sources.

Université Ibn-Tofail (MA)
Openalex Percentile: Top 79%
Robotic Path Planning Algorithms
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