Signal decomposition for wind turbine clutter mitigation

Faruk Uysal; Unnikrishna Pillai; Ivan Selesnick; Braham Himed

doi:10.1109/RADAR.2014.6875555

Signal decomposition for wind turbine clutter mitigation

Faruk Uysal, Unnikrishna Pillai, Ivan Selesnick, Braham Himed

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	2014 IEEE Radar Conference
Subtitle of host publication	From Sensing to Information, RadarCon 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	60-63
Number of pages	4
ISBN (Print)	9781479920341
DOIs	https://doi.org/10.1109/RADAR.2014.6875555
State	Published - 2014
Event	2014 IEEE Radar Conference, RadarCon 2014 - Cincinnati, OH, United States Duration: May 19 2014 → May 23 2014

Publication series

Name	IEEE National Radar Conference - Proceedings
ISSN (Print)	1097-5659

Other

Other	2014 IEEE Radar Conference, RadarCon 2014
Country/Territory	United States
City	Cincinnati, OH
Period	5/19/14 → 5/23/14

Keywords

Signal decomposition
sparse signal representation
wind turbine clutter mitigation

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/RADAR.2014.6875555

Cite this

Signal decomposition for wind turbine clutter mitigation. / Uysal, Faruk; Pillai, Unnikrishna ; Selesnick, Ivan et al.
2014 IEEE Radar Conference: From Sensing to Information, RadarCon 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 60-63 6875555 (IEEE National Radar Conference - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference 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, IEEE National Radar Conference - Proceedings, 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

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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",

series = "IEEE National Radar Conference - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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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

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PB - Institute of Electrical and Electronics Engineers Inc.

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Signal decomposition for wind turbine clutter mitigation

Abstract

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Keywords

ASJC Scopus subject areas

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