MPC-Based Dynamic Trajectory Spoofing for UAVs

Navigation spoofing has been widely utilized in unmanned aircraft vehicle (UAV) countermeasures, due to its advantages of covertness, effectiveness, and dynamic trajectory control ability. However, existing research faces two primary challenges. Firstly, sudden changes in the target UAV’s trajectory can result in a significant degradation in the spoofing performance, which may enable the onboard inertial components to detect and identify the ongoing spoofing attempts. Secondly, gradual accumulation of control errors over time degenerates the spoofing effect. To address these problems, we propose a dynamic trajectory spoofing approach for UAVs based on model predictive control (MPC), which progressively steers the UAVs towards the predetermined trajectory of the spoofer. Simulation results demonstrate a substantial enhancement in dynamic trajectory control performance and decrease in accumulation error compared to the existing methods.

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Publication Details

Journal
Drones
Published
2024-10-19
DOI
https://doi.org/10.3390/drones8100602
Citations
5
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
1.25

Funders

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MPC-Based Dynamic Trajectory Spoofing for UAVs

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1.25
article

MPC-Based Dynamic Trajectory Spoofing for UAVs

Xulei Jin, Bo Hou, Zhiliang Fan, Zhongjie Yin, Haiyang Wang
article en
5 citations

Abstract

Navigation spoofing has been widely utilized in unmanned aircraft vehicle (UAV) countermeasures, due to its advantages of covertness, effectiveness, and dynamic trajectory control ability. However, existing research faces two primary challenges. Firstly, sudden changes in the target UAV’s trajectory can result in a significant degradation in the spoofing performance, which may enable the onboard inertial components to detect and identify the ongoing spoofing attempts. Secondly, gradual accumulation of control errors over time degenerates the spoofing effect. To address these problems, we propose a dynamic trajectory spoofing approach for UAVs based on model predictive control (MPC), which progressively steers the UAVs towards the predetermined trajectory of the spoofer. Simulation results demonstrate a substantial enhancement in dynamic trajectory control performance and decrease in accumulation error compared to the existing methods.

DronesVol. 8(10)
Northwestern Polytechnical University (CN), PLA Rocket Force University of Engineering (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 19%
Robotic Path Planning Algorithms
1.25
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