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 contributionpeer-review

13 Scopus citations

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
StatePublished - 3 Nov 2017
Event2017 22nd International Conference on Digital Signal Processing, DSP 2017 - London, United Kingdom
Duration: 23 Aug 201725 Aug 2017

Publication series

NameInternational Conference on Digital Signal Processing, DSP
Volume2017-August

Conference

Conference2017 22nd International Conference on Digital Signal Processing, DSP 2017
Country/TerritoryUnited Kingdom
CityLondon
Period23/08/1725/08/17

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