Helicopter classification via period estimation and time-frequency masks

Rui Zhang, Gang Li, Carmine Clemente, Pramod K. Varshney

Research output: Contribution to conferencePaper

5 Citations (Scopus)
53 Downloads (Pure)

Abstract

The rotation of blades of a helicopter induces a Doppler modulation around the main Doppler shift, which is commonly called the micro-Doppler signature and can be used for target classification. In this paper, an automatic helicopter
classification method is proposed by estimating the period of the micro-Doppler signature and identifying the number of blades via time-frequency masks. The advantages of this method are threefold: (1) it determines the number of blades automatically; (2) it significantly reduces the computational burden compared to the classical model dictionary-based classification methods; (3) it is robust with respect to the inclination of the helicopter. The effectiveness of the proposed approach is validated by using both synthetic and real data.
Original languageEnglish
Pages61-64
Number of pages4
DOIs
Publication statusPublished - Dec 2015
Event6th IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2015) - Cancun, Mexico
Duration: 13 Dec 201516 Dec 2015

Workshop

Workshop6th IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2015)
CountryMexico
CityCancun
Period13/12/1516/12/15

Keywords

  • micro-doppler
  • helicopter classification
  • time-frequency analysis
  • radar signal processing
  • signal classification
  • doppler radar

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