Signal decomposition for wind turbine clutter mitigation

Faruk Uysal, Unnikrishna Pillai, Ivan Selesnick, Braham Himed

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

Abstract

This paper addresses the problem of dynamic clutter mitigation by focusing on the mitigation of the wind turbine clutter from the radar data. The basis pursuit and morphological component analysis approach are used to decompose the radar returns into the sum of oscillatory and transient components. The success of the morphological component analysis rely on sparsity, thus different transform domains needs to be identified correctly to represent each component sparsely. The method is illustrated on a radar data collected from a small custom built radar system to show the success of the proposed algorithm for wind turbine clutter mitigation.

Original languageEnglish (US)
Title of host publication2014 IEEE Radar Conference: From Sensing to Information, RadarCon 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages60-63
Number of pages4
ISBN (Print)9781479920341
DOIs
StatePublished - 2014
Event2014 IEEE Radar Conference, RadarCon 2014 - Cincinnati, OH, United States
Duration: May 19 2014May 23 2014

Other

Other2014 IEEE Radar Conference, RadarCon 2014
CountryUnited States
CityCincinnati, OH
Period5/19/145/23/14

Fingerprint

Wind turbines
Radar
Decomposition
Radar systems

Keywords

  • Signal decomposition
  • sparse signal representation
  • wind turbine clutter mitigation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Uysal, F., Pillai, U., Selesnick, I., & Himed, B. (2014). Signal decomposition for wind turbine clutter mitigation. In 2014 IEEE Radar Conference: From Sensing to Information, RadarCon 2014 (pp. 60-63). [6875555] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RADAR.2014.6875555

Signal decomposition for wind turbine clutter mitigation. / Uysal, Faruk; Pillai, Unnikrishna; Selesnick, Ivan; Himed, Braham.

2014 IEEE Radar Conference: From Sensing to Information, RadarCon 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 60-63 6875555.

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

Uysal, F, Pillai, U, Selesnick, I & Himed, B 2014, Signal decomposition for wind turbine clutter mitigation. in 2014 IEEE Radar Conference: From Sensing to Information, RadarCon 2014., 6875555, Institute of Electrical and Electronics Engineers Inc., pp. 60-63, 2014 IEEE Radar Conference, RadarCon 2014, Cincinnati, OH, United States, 5/19/14. https://doi.org/10.1109/RADAR.2014.6875555
Uysal F, Pillai U, Selesnick I, Himed B. Signal decomposition for wind turbine clutter mitigation. In 2014 IEEE Radar Conference: From Sensing to Information, RadarCon 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 60-63. 6875555 https://doi.org/10.1109/RADAR.2014.6875555
Uysal, Faruk ; Pillai, Unnikrishna ; Selesnick, Ivan ; Himed, Braham. / Signal decomposition for wind turbine clutter mitigation. 2014 IEEE Radar Conference: From Sensing to Information, RadarCon 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 60-63
@inproceedings{f6e418a8a177465f8c4664b6f3f3efc5,
title = "Signal decomposition for wind turbine clutter mitigation",
abstract = "This paper addresses the problem of dynamic clutter mitigation by focusing on the mitigation of the wind turbine clutter from the radar data. The basis pursuit and morphological component analysis approach are used to decompose the radar returns into the sum of oscillatory and transient components. The success of the morphological component analysis rely on sparsity, thus different transform domains needs to be identified correctly to represent each component sparsely. The method is illustrated on a radar data collected from a small custom built radar system to show the success of the proposed algorithm for wind turbine clutter mitigation.",
keywords = "Signal decomposition, sparse signal representation, wind turbine clutter mitigation",
author = "Faruk Uysal and Unnikrishna Pillai and Ivan Selesnick and Braham Himed",
year = "2014",
doi = "10.1109/RADAR.2014.6875555",
language = "English (US)",
isbn = "9781479920341",
pages = "60--63",
booktitle = "2014 IEEE Radar Conference: From Sensing to Information, RadarCon 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Signal decomposition for wind turbine clutter mitigation

AU - Uysal, Faruk

AU - Pillai, Unnikrishna

AU - Selesnick, Ivan

AU - Himed, Braham

PY - 2014

Y1 - 2014

N2 - This paper addresses the problem of dynamic clutter mitigation by focusing on the mitigation of the wind turbine clutter from the radar data. The basis pursuit and morphological component analysis approach are used to decompose the radar returns into the sum of oscillatory and transient components. The success of the morphological component analysis rely on sparsity, thus different transform domains needs to be identified correctly to represent each component sparsely. The method is illustrated on a radar data collected from a small custom built radar system to show the success of the proposed algorithm for wind turbine clutter mitigation.

AB - This paper addresses the problem of dynamic clutter mitigation by focusing on the mitigation of the wind turbine clutter from the radar data. The basis pursuit and morphological component analysis approach are used to decompose the radar returns into the sum of oscillatory and transient components. The success of the morphological component analysis rely on sparsity, thus different transform domains needs to be identified correctly to represent each component sparsely. The method is illustrated on a radar data collected from a small custom built radar system to show the success of the proposed algorithm for wind turbine clutter mitigation.

KW - Signal decomposition

KW - sparse signal representation

KW - wind turbine clutter mitigation

UR - http://www.scopus.com/inward/record.url?scp=84906706935&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84906706935&partnerID=8YFLogxK

U2 - 10.1109/RADAR.2014.6875555

DO - 10.1109/RADAR.2014.6875555

M3 - Conference contribution

SN - 9781479920341

SP - 60

EP - 63

BT - 2014 IEEE Radar Conference: From Sensing to Information, RadarCon 2014

PB - Institute of Electrical and Electronics Engineers Inc.

ER -