An EMD-based micro-Doppler signature analysis for mini-UAV blade flash reconstruction

Beom Seok Oh, Xin Guo, Fangyuan Wan, Kar Ann Toh, Zhiping Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Under a radar-based mini-size unmanned aerial vehicle (mini-UAV) classification scenario, the mini-UAV physical parameters play an important role. The parameters can be retrieved from radar blade flashes induced by rotor blades. In this work, we propose a novel method for enhancing the distinctive-ness between blade flashes so that the physical parameters can be better estimated. Essentially, the radar micro-Doppler signatures (m-DS) is decomposed using a time-frequency analysis method, empirical mode decomposition (EMD). We then reconstruct the blade flashes using the selected blade-flash-characterized mode functions. From the spectrogram, the reconstructed blade flashes can be better seen than without using EMD.

Original languageEnglish
Title of host publication2017 22nd International Conference on Digital Signal Processing, DSP 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538618950
DOIs
Publication statusPublished - 2017 Nov 3
Event2017 22nd International Conference on Digital Signal Processing, DSP 2017 - London, United Kingdom
Duration: 2017 Aug 232017 Aug 25

Publication series

NameInternational Conference on Digital Signal Processing, DSP
Volume2017-August

Other

Other2017 22nd International Conference on Digital Signal Processing, DSP 2017
CountryUnited Kingdom
CityLondon
Period17/8/2317/8/25

Fingerprint

Unmanned aerial vehicles (UAV)
Radar
Decomposition
Turbomachine blades
Rotors

All Science Journal Classification (ASJC) codes

  • Signal Processing

Cite this

Oh, B. S., Guo, X., Wan, F., Toh, K. A., & Lin, Z. (2017). An EMD-based micro-Doppler signature analysis for mini-UAV blade flash reconstruction. In 2017 22nd International Conference on Digital Signal Processing, DSP 2017 [8096105] (International Conference on Digital Signal Processing, DSP; Vol. 2017-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDSP.2017.8096105
Oh, Beom Seok ; Guo, Xin ; Wan, Fangyuan ; Toh, Kar Ann ; Lin, Zhiping. / An EMD-based micro-Doppler signature analysis for mini-UAV blade flash reconstruction. 2017 22nd International Conference on Digital Signal Processing, DSP 2017. Institute of Electrical and Electronics Engineers Inc., 2017. (International Conference on Digital Signal Processing, DSP).
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abstract = "Under a radar-based mini-size unmanned aerial vehicle (mini-UAV) classification scenario, the mini-UAV physical parameters play an important role. The parameters can be retrieved from radar blade flashes induced by rotor blades. In this work, we propose a novel method for enhancing the distinctive-ness between blade flashes so that the physical parameters can be better estimated. Essentially, the radar micro-Doppler signatures (m-DS) is decomposed using a time-frequency analysis method, empirical mode decomposition (EMD). We then reconstruct the blade flashes using the selected blade-flash-characterized mode functions. From the spectrogram, the reconstructed blade flashes can be better seen than without using EMD.",
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Oh, BS, Guo, X, Wan, F, Toh, KA & Lin, Z 2017, An EMD-based micro-Doppler signature analysis for mini-UAV blade flash reconstruction. in 2017 22nd International Conference on Digital Signal Processing, DSP 2017., 8096105, International Conference on Digital Signal Processing, DSP, vol. 2017-August, Institute of Electrical and Electronics Engineers Inc., 2017 22nd International Conference on Digital Signal Processing, DSP 2017, London, United Kingdom, 17/8/23. https://doi.org/10.1109/ICDSP.2017.8096105

An EMD-based micro-Doppler signature analysis for mini-UAV blade flash reconstruction. / Oh, Beom Seok; Guo, Xin; Wan, Fangyuan; Toh, Kar Ann; Lin, Zhiping.

2017 22nd International Conference on Digital Signal Processing, DSP 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 8096105 (International Conference on Digital Signal Processing, DSP; Vol. 2017-August).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Under a radar-based mini-size unmanned aerial vehicle (mini-UAV) classification scenario, the mini-UAV physical parameters play an important role. The parameters can be retrieved from radar blade flashes induced by rotor blades. In this work, we propose a novel method for enhancing the distinctive-ness between blade flashes so that the physical parameters can be better estimated. Essentially, the radar micro-Doppler signatures (m-DS) is decomposed using a time-frequency analysis method, empirical mode decomposition (EMD). We then reconstruct the blade flashes using the selected blade-flash-characterized mode functions. From the spectrogram, the reconstructed blade flashes can be better seen than without using EMD.

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Oh BS, Guo X, Wan F, Toh KA, Lin Z. An EMD-based micro-Doppler signature analysis for mini-UAV blade flash reconstruction. In 2017 22nd International Conference on Digital Signal Processing, DSP 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 8096105. (International Conference on Digital Signal Processing, DSP). https://doi.org/10.1109/ICDSP.2017.8096105