On estimating time offsets in the ambient noise correlation function caused by instrument response errors
Abstract Broadband seismic networks are becoming more intensive, generating a large amount of data in the long-term collection process. When processing the data, the researchers rely almost on instrument response files to understand the information related to the instrument. Aiming at the process of...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ye, Fang [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Anmerkung: |
© Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2018 |
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| Übergeordnetes Werk: |
Enthalten in: Acta geophysica - Warsaw : De Gruyter Open, 2006, 66(2018), 6 vom: 31. Okt., Seite 1291-1301 |
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| Übergeordnetes Werk: |
volume:66 ; year:2018 ; number:6 ; day:31 ; month:10 ; pages:1291-1301 |
| Links: |
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| DOI / URN: |
10.1007/s11600-018-0218-y |
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| Katalog-ID: |
SPR021025452 |
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| 245 | 1 | 0 | |a On estimating time offsets in the ambient noise correlation function caused by instrument response errors |
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| 520 | |a Abstract Broadband seismic networks are becoming more intensive, generating a large amount of data in the long-term collection process. When processing the data, the researchers rely almost on instrument response files to understand the information related to the instrument. Aiming at the process of instrument response recording and instrument response correction, we identify several sources of the instrument response phase error, including pole–zero change, the causality difference in instrument correction method, and the problem of filter coefficient recording. The data time offset range from the instrument response phase error is calculated from one sample point to several seconds using the ambient noise data recorded by multiple seismic stations. With different data delays, the time offset of the noise correlation function is estimated to be 74% to 99% of the data delay time. In addition, the influence of instrument response phase error on the measurement of seismic velocity change is analyzed by using ambient noise data with pole–zero change, and the results show that the abnormal wave velocity with exceeding the standard value is exactly in the time period of the instrument response error, which indicates that the instrument response error affects the study of seismology. | ||
| 650 | 4 | |a Time offset |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Instrument response |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Seismic ambient noise |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Seismic velocity change |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Lin, Jun |4 aut | |
| 700 | 1 | |a Zhang, Xiaopu |4 aut | |
| 700 | 1 | |a Jiang, Xiaoxue |4 aut | |
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10.1007/s11600-018-0218-y doi (DE-627)SPR021025452 (SPR)s11600-018-0218-y-e DE-627 ger DE-627 rakwb eng Ye, Fang verfasserin aut On estimating time offsets in the ambient noise correlation function caused by instrument response errors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2018 Abstract Broadband seismic networks are becoming more intensive, generating a large amount of data in the long-term collection process. When processing the data, the researchers rely almost on instrument response files to understand the information related to the instrument. Aiming at the process of instrument response recording and instrument response correction, we identify several sources of the instrument response phase error, including pole–zero change, the causality difference in instrument correction method, and the problem of filter coefficient recording. The data time offset range from the instrument response phase error is calculated from one sample point to several seconds using the ambient noise data recorded by multiple seismic stations. With different data delays, the time offset of the noise correlation function is estimated to be 74% to 99% of the data delay time. In addition, the influence of instrument response phase error on the measurement of seismic velocity change is analyzed by using ambient noise data with pole–zero change, and the results show that the abnormal wave velocity with exceeding the standard value is exactly in the time period of the instrument response error, which indicates that the instrument response error affects the study of seismology. Time offset (dpeaa)DE-He213 Instrument response (dpeaa)DE-He213 Seismic ambient noise (dpeaa)DE-He213 Seismic velocity change (dpeaa)DE-He213 Lin, Jun aut Zhang, Xiaopu aut Jiang, Xiaoxue aut Enthalten in Acta geophysica Warsaw : De Gruyter Open, 2006 66(2018), 6 vom: 31. Okt., Seite 1291-1301 (DE-627)51061843X (DE-600)2231673-5 1895-7455 nnns volume:66 year:2018 number:6 day:31 month:10 pages:1291-1301 https://dx.doi.org/10.1007/s11600-018-0218-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 66 2018 6 31 10 1291-1301 |
| spelling |
10.1007/s11600-018-0218-y doi (DE-627)SPR021025452 (SPR)s11600-018-0218-y-e DE-627 ger DE-627 rakwb eng Ye, Fang verfasserin aut On estimating time offsets in the ambient noise correlation function caused by instrument response errors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2018 Abstract Broadband seismic networks are becoming more intensive, generating a large amount of data in the long-term collection process. When processing the data, the researchers rely almost on instrument response files to understand the information related to the instrument. Aiming at the process of instrument response recording and instrument response correction, we identify several sources of the instrument response phase error, including pole–zero change, the causality difference in instrument correction method, and the problem of filter coefficient recording. The data time offset range from the instrument response phase error is calculated from one sample point to several seconds using the ambient noise data recorded by multiple seismic stations. With different data delays, the time offset of the noise correlation function is estimated to be 74% to 99% of the data delay time. In addition, the influence of instrument response phase error on the measurement of seismic velocity change is analyzed by using ambient noise data with pole–zero change, and the results show that the abnormal wave velocity with exceeding the standard value is exactly in the time period of the instrument response error, which indicates that the instrument response error affects the study of seismology. Time offset (dpeaa)DE-He213 Instrument response (dpeaa)DE-He213 Seismic ambient noise (dpeaa)DE-He213 Seismic velocity change (dpeaa)DE-He213 Lin, Jun aut Zhang, Xiaopu aut Jiang, Xiaoxue aut Enthalten in Acta geophysica Warsaw : De Gruyter Open, 2006 66(2018), 6 vom: 31. Okt., Seite 1291-1301 (DE-627)51061843X (DE-600)2231673-5 1895-7455 nnns volume:66 year:2018 number:6 day:31 month:10 pages:1291-1301 https://dx.doi.org/10.1007/s11600-018-0218-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 66 2018 6 31 10 1291-1301 |
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10.1007/s11600-018-0218-y doi (DE-627)SPR021025452 (SPR)s11600-018-0218-y-e DE-627 ger DE-627 rakwb eng Ye, Fang verfasserin aut On estimating time offsets in the ambient noise correlation function caused by instrument response errors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2018 Abstract Broadband seismic networks are becoming more intensive, generating a large amount of data in the long-term collection process. When processing the data, the researchers rely almost on instrument response files to understand the information related to the instrument. Aiming at the process of instrument response recording and instrument response correction, we identify several sources of the instrument response phase error, including pole–zero change, the causality difference in instrument correction method, and the problem of filter coefficient recording. The data time offset range from the instrument response phase error is calculated from one sample point to several seconds using the ambient noise data recorded by multiple seismic stations. With different data delays, the time offset of the noise correlation function is estimated to be 74% to 99% of the data delay time. In addition, the influence of instrument response phase error on the measurement of seismic velocity change is analyzed by using ambient noise data with pole–zero change, and the results show that the abnormal wave velocity with exceeding the standard value is exactly in the time period of the instrument response error, which indicates that the instrument response error affects the study of seismology. Time offset (dpeaa)DE-He213 Instrument response (dpeaa)DE-He213 Seismic ambient noise (dpeaa)DE-He213 Seismic velocity change (dpeaa)DE-He213 Lin, Jun aut Zhang, Xiaopu aut Jiang, Xiaoxue aut Enthalten in Acta geophysica Warsaw : De Gruyter Open, 2006 66(2018), 6 vom: 31. Okt., Seite 1291-1301 (DE-627)51061843X (DE-600)2231673-5 1895-7455 nnns volume:66 year:2018 number:6 day:31 month:10 pages:1291-1301 https://dx.doi.org/10.1007/s11600-018-0218-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 66 2018 6 31 10 1291-1301 |
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10.1007/s11600-018-0218-y doi (DE-627)SPR021025452 (SPR)s11600-018-0218-y-e DE-627 ger DE-627 rakwb eng Ye, Fang verfasserin aut On estimating time offsets in the ambient noise correlation function caused by instrument response errors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2018 Abstract Broadband seismic networks are becoming more intensive, generating a large amount of data in the long-term collection process. When processing the data, the researchers rely almost on instrument response files to understand the information related to the instrument. Aiming at the process of instrument response recording and instrument response correction, we identify several sources of the instrument response phase error, including pole–zero change, the causality difference in instrument correction method, and the problem of filter coefficient recording. The data time offset range from the instrument response phase error is calculated from one sample point to several seconds using the ambient noise data recorded by multiple seismic stations. With different data delays, the time offset of the noise correlation function is estimated to be 74% to 99% of the data delay time. In addition, the influence of instrument response phase error on the measurement of seismic velocity change is analyzed by using ambient noise data with pole–zero change, and the results show that the abnormal wave velocity with exceeding the standard value is exactly in the time period of the instrument response error, which indicates that the instrument response error affects the study of seismology. Time offset (dpeaa)DE-He213 Instrument response (dpeaa)DE-He213 Seismic ambient noise (dpeaa)DE-He213 Seismic velocity change (dpeaa)DE-He213 Lin, Jun aut Zhang, Xiaopu aut Jiang, Xiaoxue aut Enthalten in Acta geophysica Warsaw : De Gruyter Open, 2006 66(2018), 6 vom: 31. Okt., Seite 1291-1301 (DE-627)51061843X (DE-600)2231673-5 1895-7455 nnns volume:66 year:2018 number:6 day:31 month:10 pages:1291-1301 https://dx.doi.org/10.1007/s11600-018-0218-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 66 2018 6 31 10 1291-1301 |
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10.1007/s11600-018-0218-y doi (DE-627)SPR021025452 (SPR)s11600-018-0218-y-e DE-627 ger DE-627 rakwb eng Ye, Fang verfasserin aut On estimating time offsets in the ambient noise correlation function caused by instrument response errors 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2018 Abstract Broadband seismic networks are becoming more intensive, generating a large amount of data in the long-term collection process. When processing the data, the researchers rely almost on instrument response files to understand the information related to the instrument. Aiming at the process of instrument response recording and instrument response correction, we identify several sources of the instrument response phase error, including pole–zero change, the causality difference in instrument correction method, and the problem of filter coefficient recording. The data time offset range from the instrument response phase error is calculated from one sample point to several seconds using the ambient noise data recorded by multiple seismic stations. With different data delays, the time offset of the noise correlation function is estimated to be 74% to 99% of the data delay time. In addition, the influence of instrument response phase error on the measurement of seismic velocity change is analyzed by using ambient noise data with pole–zero change, and the results show that the abnormal wave velocity with exceeding the standard value is exactly in the time period of the instrument response error, which indicates that the instrument response error affects the study of seismology. Time offset (dpeaa)DE-He213 Instrument response (dpeaa)DE-He213 Seismic ambient noise (dpeaa)DE-He213 Seismic velocity change (dpeaa)DE-He213 Lin, Jun aut Zhang, Xiaopu aut Jiang, Xiaoxue aut Enthalten in Acta geophysica Warsaw : De Gruyter Open, 2006 66(2018), 6 vom: 31. Okt., Seite 1291-1301 (DE-627)51061843X (DE-600)2231673-5 1895-7455 nnns volume:66 year:2018 number:6 day:31 month:10 pages:1291-1301 https://dx.doi.org/10.1007/s11600-018-0218-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 66 2018 6 31 10 1291-1301 |
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Enthalten in Acta geophysica 66(2018), 6 vom: 31. Okt., Seite 1291-1301 volume:66 year:2018 number:6 day:31 month:10 pages:1291-1301 |
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Ye, Fang @@aut@@ Lin, Jun @@aut@@ Zhang, Xiaopu @@aut@@ Jiang, Xiaoxue @@aut@@ |
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Ye, Fang |
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Ye, Fang misc Time offset misc Instrument response misc Seismic ambient noise misc Seismic velocity change On estimating time offsets in the ambient noise correlation function caused by instrument response errors |
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On estimating time offsets in the ambient noise correlation function caused by instrument response errors Time offset (dpeaa)DE-He213 Instrument response (dpeaa)DE-He213 Seismic ambient noise (dpeaa)DE-He213 Seismic velocity change (dpeaa)DE-He213 |
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misc Time offset misc Instrument response misc Seismic ambient noise misc Seismic velocity change |
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misc Time offset misc Instrument response misc Seismic ambient noise misc Seismic velocity change |
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On estimating time offsets in the ambient noise correlation function caused by instrument response errors |
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Ye, Fang Lin, Jun Zhang, Xiaopu Jiang, Xiaoxue |
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10.1007/s11600-018-0218-y |
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on estimating time offsets in the ambient noise correlation function caused by instrument response errors |
| title_auth |
On estimating time offsets in the ambient noise correlation function caused by instrument response errors |
| abstract |
Abstract Broadband seismic networks are becoming more intensive, generating a large amount of data in the long-term collection process. When processing the data, the researchers rely almost on instrument response files to understand the information related to the instrument. Aiming at the process of instrument response recording and instrument response correction, we identify several sources of the instrument response phase error, including pole–zero change, the causality difference in instrument correction method, and the problem of filter coefficient recording. The data time offset range from the instrument response phase error is calculated from one sample point to several seconds using the ambient noise data recorded by multiple seismic stations. With different data delays, the time offset of the noise correlation function is estimated to be 74% to 99% of the data delay time. In addition, the influence of instrument response phase error on the measurement of seismic velocity change is analyzed by using ambient noise data with pole–zero change, and the results show that the abnormal wave velocity with exceeding the standard value is exactly in the time period of the instrument response error, which indicates that the instrument response error affects the study of seismology. © Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2018 |
| abstractGer |
Abstract Broadband seismic networks are becoming more intensive, generating a large amount of data in the long-term collection process. When processing the data, the researchers rely almost on instrument response files to understand the information related to the instrument. Aiming at the process of instrument response recording and instrument response correction, we identify several sources of the instrument response phase error, including pole–zero change, the causality difference in instrument correction method, and the problem of filter coefficient recording. The data time offset range from the instrument response phase error is calculated from one sample point to several seconds using the ambient noise data recorded by multiple seismic stations. With different data delays, the time offset of the noise correlation function is estimated to be 74% to 99% of the data delay time. In addition, the influence of instrument response phase error on the measurement of seismic velocity change is analyzed by using ambient noise data with pole–zero change, and the results show that the abnormal wave velocity with exceeding the standard value is exactly in the time period of the instrument response error, which indicates that the instrument response error affects the study of seismology. © Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2018 |
| abstract_unstemmed |
Abstract Broadband seismic networks are becoming more intensive, generating a large amount of data in the long-term collection process. When processing the data, the researchers rely almost on instrument response files to understand the information related to the instrument. Aiming at the process of instrument response recording and instrument response correction, we identify several sources of the instrument response phase error, including pole–zero change, the causality difference in instrument correction method, and the problem of filter coefficient recording. The data time offset range from the instrument response phase error is calculated from one sample point to several seconds using the ambient noise data recorded by multiple seismic stations. With different data delays, the time offset of the noise correlation function is estimated to be 74% to 99% of the data delay time. In addition, the influence of instrument response phase error on the measurement of seismic velocity change is analyzed by using ambient noise data with pole–zero change, and the results show that the abnormal wave velocity with exceeding the standard value is exactly in the time period of the instrument response error, which indicates that the instrument response error affects the study of seismology. © Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2018 |
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On estimating time offsets in the ambient noise correlation function caused by instrument response errors |
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https://dx.doi.org/10.1007/s11600-018-0218-y |
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Lin, Jun Zhang, Xiaopu Jiang, Xiaoxue |
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10.1007/s11600-018-0218-y |
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