Analysis and prediction of electromagnetic interference behavior level in power distribution network of UAV positioning system

Yu Daojie; Lei Shuntian; He Kai; Zhang Xia; Guo Baisen; Chai Mengjuan

doi:10.11884/HPLPB202335.220352

Volume 35 Issue 5

Apr. 2023

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Article Navigation > High Power Laser and Particle Beams > 2023 > 35(5): 053001

Yu Daojie, Lei Shuntian, He Kai, et al. Analysis and prediction of electromagnetic interference behavior level in power distribution network of UAV positioning system[J]. High Power Laser and Particle Beams, 2023, 35: 053001. doi: 10.11884/HPLPB202335.220352

Citation:

Yu Daojie, Lei Shuntian, He Kai, et al. Analysis and prediction of electromagnetic interference behavior level in power distribution network of UAV positioning system[J]. High Power Laser and Particle Beams, 2023, 35: 053001. doi: 10.11884/HPLPB202335.220352

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Analysis and prediction of electromagnetic interference behavior level in power distribution network of UAV positioning system

doi: 10.11884/HPLPB202335.220352

Yu Daojie^1
,,
Lei Shuntian¹,
He Kai^{1
,
,},
Zhang Xia¹,
Guo Baisen^{1, 2},
Chai Mengjuan¹

1.
School of Information System Engineering, Strategic Support Force Information Engineering University, Zhengzhou 450000, China
2.
School of Cyberspace Security, Zhengzhou University, Zhengzhou 450000, China

Received Date: 2022-10-24
Accepted Date: 2023-02-24
Rev Recd Date: 2023-02-24

Available Online: 2023-03-20

Publish Date: 2023-04-07

Abstract

Abstract

Power distribution network is the basic unit of unmanned aerial vehicle (UAV) positioning system, but also the weak link of electromagnetic interference (EMI). The conduction coupling interference effect of power distribution network (PDN) is the main cause of positioning system failure. To improve the accuracy of positioning system sensitivity of electromagnetic interference prediction model, based on the Taylor series description method for nonlinear systems, the Taylor series behavior level model coefficient is characterized as interference frequency related function, thus a UAV positioning system PDN electromagnetic interference response prediction model is established, which analyzes and predicts PDN’s nonlinear dc bias voltage under the circumstance of interference. The results show that the Taylor series based PDN EMI response prediction model can accurately predict the nonlinear DC bias of PDN under 250−400 MHz EMI, and the prediction error is within 3%.
- unmanned aerial vehicle,
- positioning system,
- power distribution network,
- electromagnetic interference,
- susceptibility,
- Taylor’s series

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References(17)

References

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