Pseudo-Zernike moments based radar micro-Doppler classification

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

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

8 Citations (Scopus)

Abstract

Reliable micro-Doppler signature classification requires the use of robust features describing uniquely the micromotion. 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 demonstrating the effectiveness of the proposed approach by classifying real data. 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.

Original languageEnglish
Title of host publication2014 IEEE Radar Conference
PublisherIEEE
Pages850-854
Number of pages5
ISBN (Print)978-1-4799-2034-1
DOIs
Publication statusPublished - May 2014
Event2014 IEEE Radar Conference, RadarCon 2014 - Cincinnati, OH, United States
Duration: 19 May 201423 May 2014

Conference

Conference2014 IEEE Radar Conference, RadarCon 2014
CountryUnited States
CityCincinnati, OH
Period19/05/1423/05/14

Fingerprint

Radar

Keywords

  • Doppler radar
  • Zernike polynomials
  • radar signal processing
  • signal classification

Cite this

Pallotta, Luca ; Clemente, Carmine ; De Maio, Antonio ; Soraghan, John J. ; Farina, Alfonso. / Pseudo-Zernike moments based radar micro-Doppler classification. 2014 IEEE Radar Conference. IEEE, 2014. pp. 850-854
@inproceedings{45144b067efb459896bfde032d59a464,
title = "Pseudo-Zernike moments based radar micro-Doppler classification",
abstract = "Reliable micro-Doppler signature classification requires the use of robust features describing uniquely the micromotion. 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 demonstrating the effectiveness of the proposed approach by classifying real data. 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.",
keywords = "Doppler radar, Zernike polynomials, radar signal processing, signal classification",
author = "Luca Pallotta and Carmine Clemente and {De Maio}, Antonio and Soraghan, {John J.} and Alfonso Farina",
year = "2014",
month = "5",
doi = "10.1109/RADAR.2014.6875709",
language = "English",
isbn = "978-1-4799-2034-1",
pages = "850--854",
booktitle = "2014 IEEE Radar Conference",
publisher = "IEEE",

}

Pallotta, L, Clemente, C, De Maio, A, Soraghan, JJ & Farina, A 2014, Pseudo-Zernike moments based radar micro-Doppler classification. in 2014 IEEE Radar Conference. IEEE, pp. 850-854, 2014 IEEE Radar Conference, RadarCon 2014, Cincinnati, OH, United States, 19/05/14. https://doi.org/10.1109/RADAR.2014.6875709

Pseudo-Zernike moments based radar micro-Doppler classification. / Pallotta, Luca; Clemente, Carmine; De Maio, Antonio; Soraghan, John J.; Farina, Alfonso.

2014 IEEE Radar Conference. IEEE, 2014. p. 850-854.

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

TY - GEN

T1 - Pseudo-Zernike moments based radar micro-Doppler classification

AU - Pallotta, Luca

AU - Clemente, Carmine

AU - De Maio, Antonio

AU - Soraghan, John J.

AU - Farina, Alfonso

PY - 2014/5

Y1 - 2014/5

N2 - Reliable micro-Doppler signature classification requires the use of robust features describing uniquely the micromotion. 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 demonstrating the effectiveness of the proposed approach by classifying real data. 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.

AB - Reliable micro-Doppler signature classification requires the use of robust features describing uniquely the micromotion. 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 demonstrating the effectiveness of the proposed approach by classifying real data. 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.

KW - Doppler radar

KW - Zernike polynomials

KW - radar signal processing

KW - signal classification

UR - http://www.scopus.com/inward/record.url?scp=84906748249&partnerID=8YFLogxK

U2 - 10.1109/RADAR.2014.6875709

DO - 10.1109/RADAR.2014.6875709

M3 - Conference contribution book

SN - 978-1-4799-2034-1

SP - 850

EP - 854

BT - 2014 IEEE Radar Conference

PB - IEEE

ER -