A novel algorithm for radar classification based on Doppler characteristics exploiting orthogonal pseudo-Zernike polynomials

Carmine Clemente, Luca Pallotta, Antonio De Maio, John Soraghan, Alfonso Farina

Research output: Contribution to journalArticle

56 Citations (Scopus)
166 Downloads (Pure)

Abstract

Phase modulation induced by target micro-motions introduces side-bands in the radar spectral signature returns. Time-frequency distributions facilitate the representation of such modulations in a micro-Doppler signature that is useful in the characterization and classification of targets. Reliable micro-Doppler signature classification requires the use of robust features that is capable of uniquely describing the micro-motion. Moreover, future applications of micro-Doppler classification will require meaningful representation of the observed target by using a limited set of values. In this paper, the application of
the pseudo-Zernike moments for micro-Doppler classification is introduced. Specifically, the proposed algorithm consists in the extraction of the pseudo-Zernike moments from the Cadence Velocity Diagram (CVD). The use of pseudo-Zernike moments allows invariant features to be obtained that are able to discriminate the content of two-dimensional matrices with a small number of coefficients. The analysis has been conducted both on simulated and on real radar data, demonstrating the effectiveness of the proposed approach for classification purposes.
Original languageEnglish
Pages (from-to)417-430
Number of pages14
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume51
Issue number1
DOIs
Publication statusPublished - 7 Apr 2015

Keywords

  • micro-Doppler classifications
  • radar micro-Doppler signature
  • radar Doppler Spectrum
  • automatic target recognition
  • ATR
  • orthogonal moments
  • pseudo-Zernike moments

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