GPR image decomposition using two dimensional Singular Spectrum Analysis

Branislav Vuksanovic

doi:10.1109/ISPA.2015.7306074

GPR image decomposition using two dimensional Singular Spectrum Analysis

Branislav Vuksanovic^*

^*Corresponding author for this work

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

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Abstract

Ground penetrating radar measurements can suffer from large amount of noise and clutter. Current methods, such as time gating and background averaging, mostly applied to remove reflections from air-ground interface do not perform well when removal of extraneous and very strong and non-uniform clutter signals originating from the objects in the surveyed area other than the target is needed. This work describes and evaluates performance of Singular Spectrum Analysis (SSA) and its multivariate derivatives for those tasks. Experimental GPR data using simple geometric shapes measured under laboratory conditions are used to demonstrate the effectiveness of proposed algorithm for these tasks.

Original language	English
Title of host publication	9th International Symposium on Image and Signal Processing and Analysis, ISPA 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	288-293
Number of pages	6
ISBN (Electronic)	978-1467380324
DOIs	https://doi.org/10.1109/ISPA.2015.7306074
Publication status	Published - 26 Oct 2015
Event	9th International Symposium on Image and Signal Processing and Analysis, ISPA 2015 - Zagreb, Croatia Duration: 7 Sept 2015 → 9 Sept 2015

Publication series

Name
ISSN (Print)	1845-5921

Conference

Conference	9th International Symposium on Image and Signal Processing and Analysis, ISPA 2015
Country/Territory	Croatia
City	Zagreb
Period	7/09/15 → 9/09/15

Keywords

clutter
ground penetrating radar
target
two dimensional singular spectrum analysis

Access to Document

10.1109/ISPA.2015.7306074

ISPA2015paperBV3
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Accepted author manuscript (Post-print), 494 KB

Cite this

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title = "GPR image decomposition using two dimensional Singular Spectrum Analysis",

abstract = "Ground penetrating radar measurements can suffer from large amount of noise and clutter. Current methods, such as time gating and background averaging, mostly applied to remove reflections from air-ground interface do not perform well when removal of extraneous and very strong and non-uniform clutter signals originating from the objects in the surveyed area other than the target is needed. This work describes and evaluates performance of Singular Spectrum Analysis (SSA) and its multivariate derivatives for those tasks. Experimental GPR data using simple geometric shapes measured under laboratory conditions are used to demonstrate the effectiveness of proposed algorithm for these tasks.",

keywords = "clutter, ground penetrating radar, target, two dimensional singular spectrum analysis",

author = "Branislav Vuksanovic",

year = "2015",

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doi = "10.1109/ISPA.2015.7306074",

language = "English",

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

pages = "288--293",

booktitle = "9th International Symposium on Image and Signal Processing and Analysis, ISPA 2015",

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note = "9th International Symposium on Image and Signal Processing and Analysis, ISPA 2015 ; Conference date: 07-09-2015 Through 09-09-2015",

}

Vuksanovic, B 2015, GPR image decomposition using two dimensional Singular Spectrum Analysis. in 9th International Symposium on Image and Signal Processing and Analysis, ISPA 2015., 7306074, Institute of Electrical and Electronics Engineers Inc., pp. 288-293, 9th International Symposium on Image and Signal Processing and Analysis, ISPA 2015, Zagreb, Croatia, 7/09/15. https://doi.org/10.1109/ISPA.2015.7306074

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PY - 2015/10/26

Y1 - 2015/10/26

N2 - Ground penetrating radar measurements can suffer from large amount of noise and clutter. Current methods, such as time gating and background averaging, mostly applied to remove reflections from air-ground interface do not perform well when removal of extraneous and very strong and non-uniform clutter signals originating from the objects in the surveyed area other than the target is needed. This work describes and evaluates performance of Singular Spectrum Analysis (SSA) and its multivariate derivatives for those tasks. Experimental GPR data using simple geometric shapes measured under laboratory conditions are used to demonstrate the effectiveness of proposed algorithm for these tasks.

AB - Ground penetrating radar measurements can suffer from large amount of noise and clutter. Current methods, such as time gating and background averaging, mostly applied to remove reflections from air-ground interface do not perform well when removal of extraneous and very strong and non-uniform clutter signals originating from the objects in the surveyed area other than the target is needed. This work describes and evaluates performance of Singular Spectrum Analysis (SSA) and its multivariate derivatives for those tasks. Experimental GPR data using simple geometric shapes measured under laboratory conditions are used to demonstrate the effectiveness of proposed algorithm for these tasks.

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KW - ground penetrating radar

KW - target

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M3 - Conference contribution

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BT - 9th International Symposium on Image and Signal Processing and Analysis, ISPA 2015

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 7 September 2015 through 9 September 2015

ER -

GPR image decomposition using two dimensional Singular Spectrum Analysis

Abstract

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Conference

Keywords

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