High resolution radar imaging using GPOF based data extrapolation

Ozan Doǧan; Işin Erer

doi:10.1109/IGARSS.2004.1370144

High resolution radar imaging using GPOF based data extrapolation

Ozan Doǧan^*
, Işin Erer

^*Bu çalışma için yazışmadan sorumlu yazar

Elektronik ve Hab.Müh.Bölümü

Istanbul Technical University

Araştırma çıktısı: Dergi yayını › Konferans makalesi › Hakem

6 Atıf (Scopus)

Özet

A new data extrapolation technique which utilizes pole extraction based GPOF method is proposed to fit the scattering characteristics of an object. The proposed data extrapolation method is very efficient for data extrapolation when applied to the ISAR data. Modeling the data as the superposition of complex exponential signals, GPOF and Prony methods do not guarantee a stable prediction filter like the MCM method, while Burg ensures. Meanwhile the performance of GPOF decreases with the increasing number of scattering centers but the radar images obtained using this extrapolated data is still more accurate than those obtained using the extrapolated data generated by other methods.

Orijinal dil	İngilizce
Sayfa (başlangıç-bitiş)	4470-4473
Sayfa sayısı	4
Dergi	International Geoscience and Remote Sensing Symposium (IGARSS)
Hacim	7
DOI'lar	https://doi.org/10.1109/IGARSS.2004.1370144
Yayın durumu	Yayınlandı - 2004
Etkinlik	2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 - Anchorage, AK, United States Süre: 20 Eyl 2004 → 24 Eyl 2004

Belgeye Erişim

10.1109/IGARSS.2004.1370144

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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title = "High resolution radar imaging using GPOF based data extrapolation",

abstract = "A new data extrapolation technique which utilizes pole extraction based GPOF method is proposed to fit the scattering characteristics of an object. The proposed data extrapolation method is very efficient for data extrapolation when applied to the ISAR data. Modeling the data as the superposition of complex exponential signals, GPOF and Prony methods do not guarantee a stable prediction filter like the MCM method, while Burg ensures. Meanwhile the performance of GPOF decreases with the increasing number of scattering centers but the radar images obtained using this extrapolated data is still more accurate than those obtained using the extrapolated data generated by other methods.",

keywords = "Data extrapolation, GPOF, Prony",

author = "Ozan Doǧan and I{\c s}in Erer",

year = "2004",

doi = "10.1109/IGARSS.2004.1370144",

language = "English",

volume = "7",

pages = "4470--4473",

journal = "International Geoscience and Remote Sensing Symposium (IGARSS)",

issn = "2153-6996",

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

note = "2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 ; Conference date: 20-09-2004 Through 24-09-2004",

}

TY - JOUR

T1 - High resolution radar imaging using GPOF based data extrapolation

AU - Doǧan, Ozan

AU - Erer, Işin

PY - 2004

Y1 - 2004

N2 - A new data extrapolation technique which utilizes pole extraction based GPOF method is proposed to fit the scattering characteristics of an object. The proposed data extrapolation method is very efficient for data extrapolation when applied to the ISAR data. Modeling the data as the superposition of complex exponential signals, GPOF and Prony methods do not guarantee a stable prediction filter like the MCM method, while Burg ensures. Meanwhile the performance of GPOF decreases with the increasing number of scattering centers but the radar images obtained using this extrapolated data is still more accurate than those obtained using the extrapolated data generated by other methods.

AB - A new data extrapolation technique which utilizes pole extraction based GPOF method is proposed to fit the scattering characteristics of an object. The proposed data extrapolation method is very efficient for data extrapolation when applied to the ISAR data. Modeling the data as the superposition of complex exponential signals, GPOF and Prony methods do not guarantee a stable prediction filter like the MCM method, while Burg ensures. Meanwhile the performance of GPOF decreases with the increasing number of scattering centers but the radar images obtained using this extrapolated data is still more accurate than those obtained using the extrapolated data generated by other methods.

KW - Data extrapolation

KW - GPOF

KW - Prony

UR - https://www.scopus.com/pages/publications/15944426122

U2 - 10.1109/IGARSS.2004.1370144

DO - 10.1109/IGARSS.2004.1370144

M3 - Conference article

AN - SCOPUS:15944426122

SN - 2153-6996

VL - 7

SP - 4470

EP - 4473

JO - International Geoscience and Remote Sensing Symposium (IGARSS)

JF - International Geoscience and Remote Sensing Symposium (IGARSS)

T2 - 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004

Y2 - 20 September 2004 through 24 September 2004

ER -

High resolution radar imaging using GPOF based data extrapolation

Özet

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

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