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独立全球导航卫星系统(GNSS)传感器作为速度地震仪:实时监测和地震检测。

Stand-Alone GNSS Sensors as Velocity Seismometers: Real-Time Monitoring and Earthquake Detection.

机构信息

ETH Zurich, Institute of Geodesy and Photogrammetry, 8093 Zurich, Switzerland.

出版信息

Sensors (Basel). 2018 Oct 31;18(11):3712. doi: 10.3390/s18113712.

DOI:10.3390/s18113712
PMID:30384502
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6263520/
Abstract

By means of the time derivatives of Global Navigation Satellite System (GNSS) carrier-phase measurements, the instantaneous velocity of a stand-alone, single GNSS receiver can be estimated with a high precision of a few mm/s; it is feasible to even obtain the level of tenths of mm/s. Therefore, only data from the satellite navigation message are needed, thus discarding any data from a reference network. Combining this method with an efficient movement-detection algorithm opens some interesting applications for geohazard monitoring; an example is the detection of strong earthquakes. This capability is demonstrated for a case study of the 6.5 Mw earthquake of October 30, 2016, near the city of Norcia in Italy; in that region, there are densely deployed GNSS stations. It is shown that GNSS sensors can detect seismic compressional (P) waves, which are the first to arrive at a measurement station. These findings are substantiated by a comparison with data of strong-motion (SM) seismometers. Furthermore, it is shown that the GNSS-only hypocenter localization comes close (less than a kilometer) to the solutions provided by official seismic services. Finally, we conclude that this method can provide important contributions to a real-time geohazard early-warning system.

摘要

通过全球导航卫星系统(GNSS)载波相位测量的时间导数,可以高精度地估计独立单 GNSS 接收机的瞬时速度,达到几毫米/秒的水平;甚至可以达到十分之几毫米/秒的水平。因此,只需要卫星导航消息的数据,从而丢弃任何参考网络的数据。将这种方法与高效的运动检测算法相结合,为地质灾害监测开辟了一些有趣的应用;例如,检测强震。这项能力在 2016 年 10 月 30 日意大利诺尔恰市附近发生的 6.5 级地震的案例研究中得到了验证;在该地区,有密集部署的 GNSS 站。结果表明,GNSS 传感器可以检测到地震压缩波(P 波),这些波是第一个到达测量站的波。这些发现通过与强震(SM)地震仪的数据进行比较得到了证实。此外,结果表明,GNSS 仅的震源定位接近(不到一公里)官方地震服务提供的解决方案。最后,我们得出结论,该方法可以为实时地质灾害预警系统提供重要贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/45e2400236be/sensors-18-03712-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/c9a15c97de7a/sensors-18-03712-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/83f4d23cc59d/sensors-18-03712-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/e4d696067306/sensors-18-03712-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/fb8eadbd6dd2/sensors-18-03712-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/33839431c97c/sensors-18-03712-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/45e2400236be/sensors-18-03712-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/c9a15c97de7a/sensors-18-03712-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/83f4d23cc59d/sensors-18-03712-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/e4d696067306/sensors-18-03712-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/fb8eadbd6dd2/sensors-18-03712-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/33839431c97c/sensors-18-03712-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d074/6263520/45e2400236be/sensors-18-03712-g006.jpg

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本文引用的文献

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