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 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.06.2025
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| Témata: | |
| ISSN: | 0018-9375, 1558-187X |
| On-line přístup: | Získat plný text |
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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. |
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| ISSN: | 0018-9375 1558-187X |
| DOI: | 10.1109/TEMC.2025.3550620 |