2-B Seyrek Özbaǧlanimli Modelleme ile Yüksek Çözünürlüklü Radar Görüntüleme

Bahar Özen; Işin Erer

doi:10.1109/SIU.2016.7495875

2-B Seyrek Özbaǧlanimli Modelleme ile Yüksek Çözünürlüklü Radar Görüntüleme

Translated title of the contribution: 2-D sparse autoregressive modeling for high resolution radar imaging

Bahar Özen, Işin Erer

Department of Electronics and Communication Engineering

Scientific and Technological Research Council of Turkey

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

ISAR imaging based on autoregressive (AR) model has not only spurious scattering centers but also high side lobes. Sparse AR models can be utilized for suppressing these. However, computational complexity of the BPDN with penalty sparsity approach which is employed to compute sparse AR model coefficients is high. In this work, the sparse AR model coefficients are computed by using BPDN and LASSO approaches which have less computational complexity. Spurious scattering centers and side lobes are successfully suppressed in the resulting radar images.

Translated title of the contribution	2-D sparse autoregressive modeling for high resolution radar imaging
Original language	Turkish
Title of host publication	2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	857-860
Number of pages	4
ISBN (Electronic)	9781509016792
DOIs	https://doi.org/10.1109/SIU.2016.7495875
Publication status	Published - 20 Jun 2016
Event	24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Turkey Duration: 16 May 2016 → 19 May 2016

Publication series

Name	2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

Conference

Conference	24th Signal Processing and Communication Application Conference, SIU 2016
Country/Territory	Turkey
City	Zonguldak
Period	16/05/16 → 19/05/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Access to Document

10.1109/SIU.2016.7495875

Cite this

Özen, B., & Erer, I. (2016). 2-B Seyrek Özbaǧlanimli Modelleme ile Yüksek Çözünürlüklü Radar Görüntüleme. In 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings (pp. 857-860). Article 7495875 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2016.7495875

Özen, Bahar ; Erer, Işin. / 2-B Seyrek Özbaǧlanimli Modelleme ile Yüksek Çözünürlüklü Radar Görüntüleme. 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 857-860 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings).

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title = "2-B Seyrek {\"O}zbaǧlanimli Modelleme ile Y{\"u}ksek {\c C}{\"o}z{\"u}n{\"u}rl{\"u}kl{\"u} Radar G{\"o}r{\"u}nt{\"u}leme",

abstract = "ISAR imaging based on autoregressive (AR) model has not only spurious scattering centers but also high side lobes. Sparse AR models can be utilized for suppressing these. However, computational complexity of the BPDN with penalty sparsity approach which is employed to compute sparse AR model coefficients is high. In this work, the sparse AR model coefficients are computed by using BPDN and LASSO approaches which have less computational complexity. Spurious scattering centers and side lobes are successfully suppressed in the resulting radar images.",

keywords = "AR model, BPDN, BPDN with penalty, LASSO, radar imaging, sparsity",

author = "Bahar {\"O}zen and I{\c s}in Erer",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 24th Signal Processing and Communication Application Conference, SIU 2016 ; Conference date: 16-05-2016 Through 19-05-2016",

year = "2016",

month = jun,

day = "20",

doi = "10.1109/SIU.2016.7495875",

language = "T{\"u}rk{\c c}e",

series = "2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings",

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

pages = "857--860",

booktitle = "2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings",

address = "United States",

}

Özen, B & Erer, I 2016, 2-B Seyrek Özbaǧlanimli Modelleme ile Yüksek Çözünürlüklü Radar Görüntüleme. in 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings., 7495875, 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 857-860, 24th Signal Processing and Communication Application Conference, SIU 2016, Zonguldak, Turkey, 16/05/16. https://doi.org/10.1109/SIU.2016.7495875

2-B Seyrek Özbaǧlanimli Modelleme ile Yüksek Çözünürlüklü Radar Görüntüleme. / Özen, Bahar; Erer, Işin.
2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 857-860 7495875 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - 2-B Seyrek Özbaǧlanimli Modelleme ile Yüksek Çözünürlüklü Radar Görüntüleme

AU - Özen, Bahar

AU - Erer, Işin

PY - 2016/6/20

Y1 - 2016/6/20

N2 - ISAR imaging based on autoregressive (AR) model has not only spurious scattering centers but also high side lobes. Sparse AR models can be utilized for suppressing these. However, computational complexity of the BPDN with penalty sparsity approach which is employed to compute sparse AR model coefficients is high. In this work, the sparse AR model coefficients are computed by using BPDN and LASSO approaches which have less computational complexity. Spurious scattering centers and side lobes are successfully suppressed in the resulting radar images.

AB - ISAR imaging based on autoregressive (AR) model has not only spurious scattering centers but also high side lobes. Sparse AR models can be utilized for suppressing these. However, computational complexity of the BPDN with penalty sparsity approach which is employed to compute sparse AR model coefficients is high. In this work, the sparse AR model coefficients are computed by using BPDN and LASSO approaches which have less computational complexity. Spurious scattering centers and side lobes are successfully suppressed in the resulting radar images.

KW - AR model

KW - BPDN

KW - BPDN with penalty

KW - LASSO

KW - radar imaging

KW - sparsity

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DO - 10.1109/SIU.2016.7495875

M3 - Konferans katkısı

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T3 - 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

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BT - 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 24th Signal Processing and Communication Application Conference, SIU 2016

Y2 - 16 May 2016 through 19 May 2016

ER -

Özen B, Erer I. 2-B Seyrek Özbaǧlanimli Modelleme ile Yüksek Çözünürlüklü Radar Görüntüleme. In 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 857-860. 7495875. (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings). doi: 10.1109/SIU.2016.7495875

2-B Seyrek Özbaǧlanimli Modelleme ile Yüksek Çözünürlüklü Radar Görüntüleme

Abstract

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