Assessment of EMI Effects on UAV Data Links

To assess the survivability of an unmanned aerial vehicle (UAV) in a complex electromagnetic environment, a novel method for assessing electromagnetic interference (EMI) threats to a UAV is introduced. A dataset of loss-of-lock thresholds for the UAV data link was generated through EMI injection tes...

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Bibliographic Details
Published in:IEEE transactions on electromagnetic compatibility Vol. 67; no. 3; pp. 786 - 799
Main Authors: Zhang, Xiaolu, Chen, Yazhou, Zhao, Min, Li, Yansong
Format: Journal Article
Language:English
Published: IEEE 01.06.2025
Subjects:
Attenuators
Autonomous aerial vehicles
Data link
Electromagnetic interference
electromagnetic interference (EMI) effect
extreme gradient boosting algorithm (XGBoost)
genetic algorithm (GA)
Mathematical models
Monitoring
Noise
Power generation
Predictive models
Shapley additive explanations (SHAP)
Signal generators
Spread spectrum communication
unmanned aerial vehicle (UAV)
ISSN:0018-9375, 1558-187X
Online Access:Get full text
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Summary:To assess the survivability of an unmanned aerial vehicle (UAV) in a complex electromagnetic environment, a novel method for assessing electromagnetic interference (EMI) threats to a UAV is introduced. A dataset of loss-of-lock thresholds for the UAV data link was generated through EMI injection tests. A genetic algorithm (GA)-optimized extreme gradient boosting (XGBoost) was then applied to efficiently predict these loss-of-lock thresholds. And Shapley additive explanations (SHAP) were used to measure the importance of features. Compared with K-nearest neighbor, support vector machine, decision tree, and XGBoost, GA-XGBoost shows better prediction accuracy and overall performance. Based on this, a GA-XGBoost-based assessment method was proposed to classify EMI effects into four levels using a three-level effect index. Finally, the EMI effect levels and SHAP results were used to formulate targeted anti-interference strategies. The proposed method can help to improve the anti-interference performance of UAVs.
ISSN:0018-9375
1558-187X
DOI:10.1109/TEMC.2025.3550620