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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Vydáno v:IEEE transactions on electromagnetic compatibility Ročník 67; číslo 3; s. 786 - 799
Hlavní autoři: Zhang, Xiaolu, Chen, Yazhou, Zhao, Min, Li, Yansong
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 01.06.2025
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ISSN:0018-9375, 1558-187X
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Shrnutí: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