Classification of micro-Doppler radar hand-gesture signatures by means of Chebyshev moments

Luca Pallotta, Michela Cauli, Carmine Clemente, Francesco Fioranelli, Gaetano Giunta, Alfonso Farina

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

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Abstract

In this paper a method capable of automatically classify radar signals of human hand-gestures exploiting the micro-Doppler signature is designed. In particular, the methodology focuses on the extraction of the Chebyshev moments from the cadence velocity diagram (CVD) of each recorded signal. The algorithm benefits from interesting properties of these moments such as the fact that they are defined on a discrete set and hence computed without approximations, as well as the symmetry property that allows to minimize the computational time. The experiments computed on the challenging real-recorded DopNet dataset show interesting results that confirm the effectiveness of the approach
Original languageEnglish
Title of host publication2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)
Place of PublicationNew York, NY
PublisherIEEE
Pages182-187
Number of pages6
ISBN (Electronic)9781728175560
ISBN (Print)9781728175577
DOIs
Publication statusPublished - 19 Aug 2021

Publication series

NameIEEE International Workshop on Metrology for Aerospace
PublisherIEEE
ISSN (Print)2575-7482
ISSN (Electronic)2575-7490

Keywords

  • micro-Doppler
  • hand-gesture recognition
  • image moments
  • millimeter wave
  • automatic target recognition (ATR)

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