High resolution radar imaging using GPOF based data extrapolation

Ozan Doǧan; Işin Erer

High resolution radar imaging using GPOF based data extrapolation

Ozan Doǧan^*, Işin Erer

^*Corresponding author for this work

Department of Electronics and Communication Engineering

Istanbul Technical University

Research output: Contribution to conference › Paper › peer-review

6 Citations (Scopus)

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.

Original language	English
Pages	4470-4473
Number of pages	4
Publication status	Published - 2004
Event	2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 - Anchorage, AK, United States Duration: 20 Sept 2004 → 24 Sept 2004

Conference

Conference	2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004
Country/Territory	United States
City	Anchorage, AK
Period	20/09/04 → 24/09/04

Keywords

Data extrapolation
GPOF
Prony

Cite this

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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",

language = "English",

pages = "4470--4473",

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",

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High resolution radar imaging using GPOF based data extrapolation. / Doǧan, Ozan; Erer, Işin.
2004. 4470-4473 Paper presented at 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004, Anchorage, AK, United States.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

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 - http://www.scopus.com/inward/record.url?scp=15944426122&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:15944426122

SP - 4470

EP - 4473

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

Abstract

Conference

Keywords

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