scholarly journals Estimating the Rayleigh-wave impulse response between seismic stations with the cross terms of the Green tensor

2011 ◽  
Vol 38 (16) ◽  
pp. n/a-n/a ◽  
Author(s):  
Kasper van Wijk ◽  
T. Dylan Mikesell ◽  
Vera Schulte-Pelkum ◽  
Josh Stachnik
Keyword(s):  
Rayleigh Wave ◽  
Impulse Response ◽  
Green Tensor ◽  
Seismic Stations ◽  
Cross Terms ◽  
The Cross

On the cross-terms in LPPs

2009 ◽  
Author(s):  
Xinbo Li ◽  
Youyi Wang ◽  
Guoan Bi ◽  
Yaowu Shi ◽  
Xiumei Li
Keyword(s):  
Cross Terms ◽  
The Cross

scholarly journals Separating body and Rayleigh waves with cross terms of the cross‐correlation tensor of ambient noise

2014 ◽  
Vol 119 (3) ◽  
pp. 2005-2018 ◽  
Author(s):  
Ryota Takagi ◽  
Hisashi Nakahara ◽  
Toshio Kono ◽  
Tomomi Okada
Keyword(s):  
Rayleigh Waves ◽  
Ambient Noise ◽  
Cross Correlation ◽  
Correlation Tensor ◽  
Cross Terms ◽  
The Cross

Estimations of Sensor Misorientation for Broadband Seismic Stations in and around Africa

2019 ◽  
Vol 90 (6) ◽  
pp. 2188-2204 ◽  
Author(s):  
Adebayo Oluwaseun Ojo ◽  
Li Zhao ◽  
Xin Wang
Keyword(s):  
Rayleigh Wave ◽  
Correlation Coefficients ◽  
Principal Component ◽  
Transverse Component ◽  
P Wave ◽  
Estimation Methods ◽  
Seismic Stations ◽  
Sensor Orientation ◽  
High Consistency ◽  
Misorientation Angles

ABSTRACT To ensure the accuracy of future seismological studies using horizontal‐component data recorded by broadband seismic stations in Africa and environs, we investigate the sensor orientation of 1075 stations belonging to 41 seismic networks deployed in and around the African continent in the past three decades. We applied three independent waveform‐based orientation estimation methods that involve the measurement of P‐wave particle motion based on the principal component analysis, minimizing the P‐wave energy on the transverse component of motion, and measuring intermediate‐period Rayleigh‐wave arrival angles from teleseismic earthquakes. We found that 34.3%–43.5% of the stations are well oriented within 3°, 40%–48.2% have sensor misorientation values between 3° and 10°, whereas 16.5%–18% of the stations are misaligned by more than 10°, most likely true sensor misorientation. The fairly high correlation coefficients (0.71–0.93) and very small mean (−0.01°–0.06°) and median (−0.04°–0.3°) differences suggest a high consistency among the estimates from the three methods. Likewise, the comparison of our results with reported orientations in the metadata at 33 stations demonstrates the robustness of the results obtained in this study. Likewise, the increase in the cross‐correlation coefficients and reduced time shifts between the Rayleigh‐wave signals on the vertical and Hilbert‐transformed radial components when the sensor misorientation angles are corrected show the importance of this study. An investigation of the time dependence of the estimated misorientation angles over the validation period reveals that the sensor orientation remained fairly constant for most stations included in the study. The nearly 180° sensor misorientation angles obtained at some stations led to the suspicion of possible polarity reversal of the seismometer components and/or channel mislabeling that was confirmed with a network manager for two of the seismic stations. Result of this study serves as a reference for future data users and a reminder to seismic network managers to decrease the number of errors that may lead to misorientations in future deployments.

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