Singular spectrum analysis and envelope detection: methods of enhancing the utility of ground-penetrating radar data

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

Singular spectrum analysis and envelope detection: methods of enhancing the utility of ground-penetrating radar data. / Moore, J; Grinsted, Aslak.

In: Journal of Glaciology, Vol. 52, No. 176, 2006, p. 159-163.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Moore, J & Grinsted, A 2006, 'Singular spectrum analysis and envelope detection: methods of enhancing the utility of ground-penetrating radar data', Journal of Glaciology, vol. 52, no. 176, pp. 159-163.

APA

Moore, J., & Grinsted, A. (2006). Singular spectrum analysis and envelope detection: methods of enhancing the utility of ground-penetrating radar data. Journal of Glaciology, 52(176), 159-163.

Vancouver

Moore J, Grinsted A. Singular spectrum analysis and envelope detection: methods of enhancing the utility of ground-penetrating radar data. Journal of Glaciology. 2006;52(176):159-163.

Author

Moore, J ; Grinsted, Aslak. / Singular spectrum analysis and envelope detection: methods of enhancing the utility of ground-penetrating radar data. In: Journal of Glaciology. 2006 ; Vol. 52, No. 176. pp. 159-163.

Bibtex

@article{4e835e30e62a11ddbf70000ea68e967b,
title = "Singular spectrum analysis and envelope detection: methods of enhancing the utility of ground-penetrating radar data",
abstract = "We present a novel method of improving signal-to-noise ratio in radargrams. The method uses singular spectrum analysis (SSA) to separate each individual radar trace into orthogonal components. The components that explain most of the original trace variance contain mainly physically meaningful signal, while the components with little variance tend to be noise. Adding the largest-magnitude components together until the sum of components accounts for the variance above the noise level (typically 60-80% %) of the original trace variance results in a much cleaner radargram with more easily seen internal features than in traditionally filtered data. The radargrams can be further enhanced by envelope-detecting the SSA-filtered data, as this measure of instantaneous energy minimizes the deleterious effects of innumerable phase changes at dielectric boundaries. Subsequent incoherent stacking results in far more structured radargrams than are achieved with traditionally processed radar data and amplitude stacking.",
author = "J Moore and Aslak Grinsted",
note = "Paper id:: 10.3189/172756506781828863",
year = "2006",
language = "English",
volume = "52",
pages = "159--163",
journal = "Journal of Glaciology",
issn = "0022-1430",
publisher = "International Glaciological Society",
number = "176",

}

RIS

TY - JOUR

T1 - Singular spectrum analysis and envelope detection: methods of enhancing the utility of ground-penetrating radar data

AU - Moore, J

AU - Grinsted, Aslak

N1 - Paper id:: 10.3189/172756506781828863

PY - 2006

Y1 - 2006

N2 - We present a novel method of improving signal-to-noise ratio in radargrams. The method uses singular spectrum analysis (SSA) to separate each individual radar trace into orthogonal components. The components that explain most of the original trace variance contain mainly physically meaningful signal, while the components with little variance tend to be noise. Adding the largest-magnitude components together until the sum of components accounts for the variance above the noise level (typically 60-80% %) of the original trace variance results in a much cleaner radargram with more easily seen internal features than in traditionally filtered data. The radargrams can be further enhanced by envelope-detecting the SSA-filtered data, as this measure of instantaneous energy minimizes the deleterious effects of innumerable phase changes at dielectric boundaries. Subsequent incoherent stacking results in far more structured radargrams than are achieved with traditionally processed radar data and amplitude stacking.

AB - We present a novel method of improving signal-to-noise ratio in radargrams. The method uses singular spectrum analysis (SSA) to separate each individual radar trace into orthogonal components. The components that explain most of the original trace variance contain mainly physically meaningful signal, while the components with little variance tend to be noise. Adding the largest-magnitude components together until the sum of components accounts for the variance above the noise level (typically 60-80% %) of the original trace variance results in a much cleaner radargram with more easily seen internal features than in traditionally filtered data. The radargrams can be further enhanced by envelope-detecting the SSA-filtered data, as this measure of instantaneous energy minimizes the deleterious effects of innumerable phase changes at dielectric boundaries. Subsequent incoherent stacking results in far more structured radargrams than are achieved with traditionally processed radar data and amplitude stacking.

M3 - Journal article

VL - 52

SP - 159

EP - 163

JO - Journal of Glaciology

JF - Journal of Glaciology

SN - 0022-1430

IS - 176

ER -

ID: 9832324