Cross-correlation beamforming
An areal distribution of sensors can be used for estimating the direction of incoming waves through beamforming. Beamforming may be implemented as a phase-shifting and stacking of data recorded on the different sensors (i.e., conventional beamforming). Alternatively, beamforming can be applied to cr...
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ftunivutrecht:oai:dspace.library.uu.nl:1874/361673 2023-11-12T04:27:04+01:00 Cross-correlation beamforming Ruigrok, Elmer Gibbons, Steven Wapenaar, Kees Seismology 2017-05 image/pdf https://dspace.library.uu.nl/handle/1874/361673 en eng 1383-4649 https://dspace.library.uu.nl/handle/1874/361673 info:eu-repo/semantics/OpenAccess Beamforming · Cross-correlation · Waveform characterization Article 2017 ftunivutrecht 2023-11-01T23:16:20Z An areal distribution of sensors can be used for estimating the direction of incoming waves through beamforming. Beamforming may be implemented as a phase-shifting and stacking of data recorded on the different sensors (i.e., conventional beamforming). Alternatively, beamforming can be applied to cross-correlations between the waveforms on the different sensors. We derive a kernel for beamforming cross-correlated data and call it cross-correlation beamforming (CCBF). We point out that CCBF has slightly better resolution and aliasing characteristics than conventional beamforming. When auto-correlations are added to CCBF, the array response functions are the same as for conventional beamforming. We show numerically that CCBF is more resilient to non-coherent noise. Furthermore, we illustrate that with CCBF individual receiver-pairs can be removed to improve mapping to the slowness domain. An additional flexibility of CCBF is that cross-correlations can be time-windowed prior to beamforming, e.g., to remove the directionality of a scattered wavefield. The observations on synthetic data are confirmed with field data from the SPITS array (Svalbard). Both when beamforming an earthquake arrival and when beamforming ambient noise, CCBF focuses more of the energy to a central beam. Overall, the main advantage of CCBF is noise suppression and its flexibility to remove station pairs that deteriorate the signal-related beampower. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10950-016-9612-6) contains supplementary material, which is available to authorized users. Article in Journal/Newspaper Svalbard Utrecht University Repository Svalbard |
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Open Polar |
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Utrecht University Repository |
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ftunivutrecht |
language |
English |
topic |
Beamforming · Cross-correlation · Waveform characterization |
spellingShingle |
Beamforming · Cross-correlation · Waveform characterization Ruigrok, Elmer Gibbons, Steven Wapenaar, Kees Cross-correlation beamforming |
topic_facet |
Beamforming · Cross-correlation · Waveform characterization |
description |
An areal distribution of sensors can be used for estimating the direction of incoming waves through beamforming. Beamforming may be implemented as a phase-shifting and stacking of data recorded on the different sensors (i.e., conventional beamforming). Alternatively, beamforming can be applied to cross-correlations between the waveforms on the different sensors. We derive a kernel for beamforming cross-correlated data and call it cross-correlation beamforming (CCBF). We point out that CCBF has slightly better resolution and aliasing characteristics than conventional beamforming. When auto-correlations are added to CCBF, the array response functions are the same as for conventional beamforming. We show numerically that CCBF is more resilient to non-coherent noise. Furthermore, we illustrate that with CCBF individual receiver-pairs can be removed to improve mapping to the slowness domain. An additional flexibility of CCBF is that cross-correlations can be time-windowed prior to beamforming, e.g., to remove the directionality of a scattered wavefield. The observations on synthetic data are confirmed with field data from the SPITS array (Svalbard). Both when beamforming an earthquake arrival and when beamforming ambient noise, CCBF focuses more of the energy to a central beam. Overall, the main advantage of CCBF is noise suppression and its flexibility to remove station pairs that deteriorate the signal-related beampower. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10950-016-9612-6) contains supplementary material, which is available to authorized users. |
author2 |
Seismology |
format |
Article in Journal/Newspaper |
author |
Ruigrok, Elmer Gibbons, Steven Wapenaar, Kees |
author_facet |
Ruigrok, Elmer Gibbons, Steven Wapenaar, Kees |
author_sort |
Ruigrok, Elmer |
title |
Cross-correlation beamforming |
title_short |
Cross-correlation beamforming |
title_full |
Cross-correlation beamforming |
title_fullStr |
Cross-correlation beamforming |
title_full_unstemmed |
Cross-correlation beamforming |
title_sort |
cross-correlation beamforming |
publishDate |
2017 |
url |
https://dspace.library.uu.nl/handle/1874/361673 |
geographic |
Svalbard |
geographic_facet |
Svalbard |
genre |
Svalbard |
genre_facet |
Svalbard |
op_relation |
1383-4649 https://dspace.library.uu.nl/handle/1874/361673 |
op_rights |
info:eu-repo/semantics/OpenAccess |
_version_ |
1782340809038757888 |