An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data

<p<In spread spectrum induced polarization (SSIP) data processing, attenuation of background noise from the observed data is the essential step that improves the signal-to-noise ratio (SNR) of SSIP data. The time-domain spectral induced polarization based on pseudorandom sequence (TSIP) algori...
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Autor*in:	S. He [verfasserIn] J. Guan [verfasserIn] X. Ji [verfasserIn] H. Xu [verfasserIn] Y. Wang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Übergeordnetes Werk:	In: Nonlinear Processes in Geophysics - Copernicus Publications, 2004, 28(2021), Seite 247-256
Übergeordnetes Werk:	volume:28 ; year:2021 ; pages:247-256

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.5194/npg-28-247-2021

Katalog-ID:	DOAJ072549971

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allfields	10.5194/npg-28-247-2021 doi (DE-627)DOAJ072549971 (DE-599)DOAJ6402d680bf4c4565a1e4e6360c1a24bc DE-627 ger DE-627 rakwb eng QC1-999 QC801-809 S. He verfasserin aut An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<In spread spectrum induced polarization (SSIP) data processing, attenuation of background noise from the observed data is the essential step that improves the signal-to-noise ratio (SNR) of SSIP data. The time-domain spectral induced polarization based on pseudorandom sequence (TSIP) algorithm has been proposed to improve the SNR of these data. However, signal processing in background noise is still a challenging problem. We propose an enhanced correlation identification (ECI) algorithm to attenuate the background noise. In this algorithm, the cross-correlation matching method is helpful for the extraction of useful components of the raw SSIP data and suppression of background noise. Then the frequency-domain IP (FDIP) method is used for extracting the frequency response of the observation system. Experiments on both synthetic and real SSIP data show that the ECI algorithm will not only suppress the background noise but also better preserve the valid information of the raw SSIP data to display the actual location and shape of adjacent high-resistivity anomalies, which can improve subsequent steps in SSIP data processing and imaging.</p< Science Q Physics Geophysics. Cosmic physics S. He verfasserin aut J. Guan verfasserin aut X. Ji verfasserin aut X. Ji verfasserin aut H. Xu verfasserin aut Y. Wang verfasserin aut In Nonlinear Processes in Geophysics Copernicus Publications, 2004 28(2021), Seite 247-256 (DE-627)347038786 (DE-600)2078085-0 16077946 nnns volume:28 year:2021 pages:247-256 https://doi.org/10.5194/npg-28-247-2021 kostenfrei https://doaj.org/article/6402d680bf4c4565a1e4e6360c1a24bc kostenfrei https://npg.copernicus.org/articles/28/247/2021/npg-28-247-2021.pdf kostenfrei https://doaj.org/toc/1023-5809 Journal toc kostenfrei https://doaj.org/toc/1607-7946 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2021 247-256
spelling	10.5194/npg-28-247-2021 doi (DE-627)DOAJ072549971 (DE-599)DOAJ6402d680bf4c4565a1e4e6360c1a24bc DE-627 ger DE-627 rakwb eng QC1-999 QC801-809 S. He verfasserin aut An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<In spread spectrum induced polarization (SSIP) data processing, attenuation of background noise from the observed data is the essential step that improves the signal-to-noise ratio (SNR) of SSIP data. The time-domain spectral induced polarization based on pseudorandom sequence (TSIP) algorithm has been proposed to improve the SNR of these data. However, signal processing in background noise is still a challenging problem. We propose an enhanced correlation identification (ECI) algorithm to attenuate the background noise. In this algorithm, the cross-correlation matching method is helpful for the extraction of useful components of the raw SSIP data and suppression of background noise. Then the frequency-domain IP (FDIP) method is used for extracting the frequency response of the observation system. Experiments on both synthetic and real SSIP data show that the ECI algorithm will not only suppress the background noise but also better preserve the valid information of the raw SSIP data to display the actual location and shape of adjacent high-resistivity anomalies, which can improve subsequent steps in SSIP data processing and imaging.</p< Science Q Physics Geophysics. Cosmic physics S. He verfasserin aut J. Guan verfasserin aut X. Ji verfasserin aut X. Ji verfasserin aut H. Xu verfasserin aut Y. Wang verfasserin aut In Nonlinear Processes in Geophysics Copernicus Publications, 2004 28(2021), Seite 247-256 (DE-627)347038786 (DE-600)2078085-0 16077946 nnns volume:28 year:2021 pages:247-256 https://doi.org/10.5194/npg-28-247-2021 kostenfrei https://doaj.org/article/6402d680bf4c4565a1e4e6360c1a24bc kostenfrei https://npg.copernicus.org/articles/28/247/2021/npg-28-247-2021.pdf kostenfrei https://doaj.org/toc/1023-5809 Journal toc kostenfrei https://doaj.org/toc/1607-7946 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2021 247-256
allfields_unstemmed	10.5194/npg-28-247-2021 doi (DE-627)DOAJ072549971 (DE-599)DOAJ6402d680bf4c4565a1e4e6360c1a24bc DE-627 ger DE-627 rakwb eng QC1-999 QC801-809 S. He verfasserin aut An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<In spread spectrum induced polarization (SSIP) data processing, attenuation of background noise from the observed data is the essential step that improves the signal-to-noise ratio (SNR) of SSIP data. The time-domain spectral induced polarization based on pseudorandom sequence (TSIP) algorithm has been proposed to improve the SNR of these data. However, signal processing in background noise is still a challenging problem. We propose an enhanced correlation identification (ECI) algorithm to attenuate the background noise. In this algorithm, the cross-correlation matching method is helpful for the extraction of useful components of the raw SSIP data and suppression of background noise. Then the frequency-domain IP (FDIP) method is used for extracting the frequency response of the observation system. Experiments on both synthetic and real SSIP data show that the ECI algorithm will not only suppress the background noise but also better preserve the valid information of the raw SSIP data to display the actual location and shape of adjacent high-resistivity anomalies, which can improve subsequent steps in SSIP data processing and imaging.</p< Science Q Physics Geophysics. Cosmic physics S. He verfasserin aut J. Guan verfasserin aut X. Ji verfasserin aut X. Ji verfasserin aut H. Xu verfasserin aut Y. Wang verfasserin aut In Nonlinear Processes in Geophysics Copernicus Publications, 2004 28(2021), Seite 247-256 (DE-627)347038786 (DE-600)2078085-0 16077946 nnns volume:28 year:2021 pages:247-256 https://doi.org/10.5194/npg-28-247-2021 kostenfrei https://doaj.org/article/6402d680bf4c4565a1e4e6360c1a24bc kostenfrei https://npg.copernicus.org/articles/28/247/2021/npg-28-247-2021.pdf kostenfrei https://doaj.org/toc/1023-5809 Journal toc kostenfrei https://doaj.org/toc/1607-7946 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2021 247-256
allfieldsGer	10.5194/npg-28-247-2021 doi (DE-627)DOAJ072549971 (DE-599)DOAJ6402d680bf4c4565a1e4e6360c1a24bc DE-627 ger DE-627 rakwb eng QC1-999 QC801-809 S. He verfasserin aut An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<In spread spectrum induced polarization (SSIP) data processing, attenuation of background noise from the observed data is the essential step that improves the signal-to-noise ratio (SNR) of SSIP data. The time-domain spectral induced polarization based on pseudorandom sequence (TSIP) algorithm has been proposed to improve the SNR of these data. However, signal processing in background noise is still a challenging problem. We propose an enhanced correlation identification (ECI) algorithm to attenuate the background noise. In this algorithm, the cross-correlation matching method is helpful for the extraction of useful components of the raw SSIP data and suppression of background noise. Then the frequency-domain IP (FDIP) method is used for extracting the frequency response of the observation system. Experiments on both synthetic and real SSIP data show that the ECI algorithm will not only suppress the background noise but also better preserve the valid information of the raw SSIP data to display the actual location and shape of adjacent high-resistivity anomalies, which can improve subsequent steps in SSIP data processing and imaging.</p< Science Q Physics Geophysics. Cosmic physics S. He verfasserin aut J. Guan verfasserin aut X. Ji verfasserin aut X. Ji verfasserin aut H. Xu verfasserin aut Y. Wang verfasserin aut In Nonlinear Processes in Geophysics Copernicus Publications, 2004 28(2021), Seite 247-256 (DE-627)347038786 (DE-600)2078085-0 16077946 nnns volume:28 year:2021 pages:247-256 https://doi.org/10.5194/npg-28-247-2021 kostenfrei https://doaj.org/article/6402d680bf4c4565a1e4e6360c1a24bc kostenfrei https://npg.copernicus.org/articles/28/247/2021/npg-28-247-2021.pdf kostenfrei https://doaj.org/toc/1023-5809 Journal toc kostenfrei https://doaj.org/toc/1607-7946 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2021 247-256
allfieldsSound	10.5194/npg-28-247-2021 doi (DE-627)DOAJ072549971 (DE-599)DOAJ6402d680bf4c4565a1e4e6360c1a24bc DE-627 ger DE-627 rakwb eng QC1-999 QC801-809 S. He verfasserin aut An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<In spread spectrum induced polarization (SSIP) data processing, attenuation of background noise from the observed data is the essential step that improves the signal-to-noise ratio (SNR) of SSIP data. The time-domain spectral induced polarization based on pseudorandom sequence (TSIP) algorithm has been proposed to improve the SNR of these data. However, signal processing in background noise is still a challenging problem. We propose an enhanced correlation identification (ECI) algorithm to attenuate the background noise. In this algorithm, the cross-correlation matching method is helpful for the extraction of useful components of the raw SSIP data and suppression of background noise. Then the frequency-domain IP (FDIP) method is used for extracting the frequency response of the observation system. Experiments on both synthetic and real SSIP data show that the ECI algorithm will not only suppress the background noise but also better preserve the valid information of the raw SSIP data to display the actual location and shape of adjacent high-resistivity anomalies, which can improve subsequent steps in SSIP data processing and imaging.</p< Science Q Physics Geophysics. Cosmic physics S. He verfasserin aut J. Guan verfasserin aut X. Ji verfasserin aut X. Ji verfasserin aut H. Xu verfasserin aut Y. Wang verfasserin aut In Nonlinear Processes in Geophysics Copernicus Publications, 2004 28(2021), Seite 247-256 (DE-627)347038786 (DE-600)2078085-0 16077946 nnns volume:28 year:2021 pages:247-256 https://doi.org/10.5194/npg-28-247-2021 kostenfrei https://doaj.org/article/6402d680bf4c4565a1e4e6360c1a24bc kostenfrei https://npg.copernicus.org/articles/28/247/2021/npg-28-247-2021.pdf kostenfrei https://doaj.org/toc/1023-5809 Journal toc kostenfrei https://doaj.org/toc/1607-7946 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2021 247-256
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He</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="3"><subfield code="a">An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a"><p<In spread spectrum induced polarization (SSIP) data processing, attenuation of background noise from the observed data is the essential step that improves the signal-to-noise ratio (SNR) of SSIP data. 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callnumber-first	Q - Science
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spellingShingle	S. He misc QC1-999 misc QC801-809 misc Science misc Q misc Physics misc Geophysics. Cosmic physics An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data
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title	An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data
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title_full	An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data
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title_sort	enhanced correlation identification algorithm and its application on spread spectrum induced polarization data
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title_auth	An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data
abstract	<p<In spread spectrum induced polarization (SSIP) data processing, attenuation of background noise from the observed data is the essential step that improves the signal-to-noise ratio (SNR) of SSIP data. The time-domain spectral induced polarization based on pseudorandom sequence (TSIP) algorithm has been proposed to improve the SNR of these data. However, signal processing in background noise is still a challenging problem. We propose an enhanced correlation identification (ECI) algorithm to attenuate the background noise. In this algorithm, the cross-correlation matching method is helpful for the extraction of useful components of the raw SSIP data and suppression of background noise. Then the frequency-domain IP (FDIP) method is used for extracting the frequency response of the observation system. Experiments on both synthetic and real SSIP data show that the ECI algorithm will not only suppress the background noise but also better preserve the valid information of the raw SSIP data to display the actual location and shape of adjacent high-resistivity anomalies, which can improve subsequent steps in SSIP data processing and imaging.</p<
abstractGer	<p<In spread spectrum induced polarization (SSIP) data processing, attenuation of background noise from the observed data is the essential step that improves the signal-to-noise ratio (SNR) of SSIP data. The time-domain spectral induced polarization based on pseudorandom sequence (TSIP) algorithm has been proposed to improve the SNR of these data. However, signal processing in background noise is still a challenging problem. We propose an enhanced correlation identification (ECI) algorithm to attenuate the background noise. In this algorithm, the cross-correlation matching method is helpful for the extraction of useful components of the raw SSIP data and suppression of background noise. Then the frequency-domain IP (FDIP) method is used for extracting the frequency response of the observation system. Experiments on both synthetic and real SSIP data show that the ECI algorithm will not only suppress the background noise but also better preserve the valid information of the raw SSIP data to display the actual location and shape of adjacent high-resistivity anomalies, which can improve subsequent steps in SSIP data processing and imaging.</p<
abstract_unstemmed	<p<In spread spectrum induced polarization (SSIP) data processing, attenuation of background noise from the observed data is the essential step that improves the signal-to-noise ratio (SNR) of SSIP data. The time-domain spectral induced polarization based on pseudorandom sequence (TSIP) algorithm has been proposed to improve the SNR of these data. However, signal processing in background noise is still a challenging problem. We propose an enhanced correlation identification (ECI) algorithm to attenuate the background noise. In this algorithm, the cross-correlation matching method is helpful for the extraction of useful components of the raw SSIP data and suppression of background noise. Then the frequency-domain IP (FDIP) method is used for extracting the frequency response of the observation system. Experiments on both synthetic and real SSIP data show that the ECI algorithm will not only suppress the background noise but also better preserve the valid information of the raw SSIP data to display the actual location and shape of adjacent high-resistivity anomalies, which can improve subsequent steps in SSIP data processing and imaging.</p<
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title_short	An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data
url	https://doi.org/10.5194/npg-28-247-2021 https://doaj.org/article/6402d680bf4c4565a1e4e6360c1a24bc https://npg.copernicus.org/articles/28/247/2021/npg-28-247-2021.pdf https://doaj.org/toc/1023-5809 https://doaj.org/toc/1607-7946
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An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data

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