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mGEODAR—A Mobile Radar System for Detection and Monitoring of Gravitational Mass-Movements
Radar measurements of gravitational mass-movements like snow avalanches have become increasingly important for scientific flow observations, real-time detection and monitoring. Independence of visibility is a main advantage for rapid and reliable detection of those events, and achievable high-resolu...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664914/ https://www.ncbi.nlm.nih.gov/pubmed/33182236 http://dx.doi.org/10.3390/s20216373 |
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author | Köhler, Anselm Lok, Lai Bun Felbermayr, Simon Peters, Nial Brennan, Paul V. Fischer, Jan-Thomas |
author_facet | Köhler, Anselm Lok, Lai Bun Felbermayr, Simon Peters, Nial Brennan, Paul V. Fischer, Jan-Thomas |
author_sort | Köhler, Anselm |
collection | PubMed |
description | Radar measurements of gravitational mass-movements like snow avalanches have become increasingly important for scientific flow observations, real-time detection and monitoring. Independence of visibility is a main advantage for rapid and reliable detection of those events, and achievable high-resolution imaging proves invaluable for scientific measurements of the complete flow evolution. Existing radar systems are made for either detection with low-resolution or they are large devices and permanently installed at test-sites. We present mGEODAR, a mobile FMCW (frequency modulated continuous wave) radar system for high-resolution measurements and low-resolution gravitational mass-movement detection and monitoring purposes due to a versatile frequency generation scheme. We optimize the performance of different frequency settings with loop cable measurements and show the freespace range sensitivity with data of a car as moving point source. About 15 dB signal-to-noise ratio is achieved for the cable test and about 5 dB or 10 dB for the car in detection and research mode, respectively. By combining continuous recording in the low resolution detection mode with real-time triggering of the high resolution research mode, we expect that mGEODAR enables autonomous measurement campaigns for infrastructure safety and mass-movement research purposes in rapid response to changing weather and snow conditions. |
format | Online Article Text |
id | pubmed-7664914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76649142020-11-14 mGEODAR—A Mobile Radar System for Detection and Monitoring of Gravitational Mass-Movements Köhler, Anselm Lok, Lai Bun Felbermayr, Simon Peters, Nial Brennan, Paul V. Fischer, Jan-Thomas Sensors (Basel) Article Radar measurements of gravitational mass-movements like snow avalanches have become increasingly important for scientific flow observations, real-time detection and monitoring. Independence of visibility is a main advantage for rapid and reliable detection of those events, and achievable high-resolution imaging proves invaluable for scientific measurements of the complete flow evolution. Existing radar systems are made for either detection with low-resolution or they are large devices and permanently installed at test-sites. We present mGEODAR, a mobile FMCW (frequency modulated continuous wave) radar system for high-resolution measurements and low-resolution gravitational mass-movement detection and monitoring purposes due to a versatile frequency generation scheme. We optimize the performance of different frequency settings with loop cable measurements and show the freespace range sensitivity with data of a car as moving point source. About 15 dB signal-to-noise ratio is achieved for the cable test and about 5 dB or 10 dB for the car in detection and research mode, respectively. By combining continuous recording in the low resolution detection mode with real-time triggering of the high resolution research mode, we expect that mGEODAR enables autonomous measurement campaigns for infrastructure safety and mass-movement research purposes in rapid response to changing weather and snow conditions. MDPI 2020-11-09 /pmc/articles/PMC7664914/ /pubmed/33182236 http://dx.doi.org/10.3390/s20216373 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Köhler, Anselm Lok, Lai Bun Felbermayr, Simon Peters, Nial Brennan, Paul V. Fischer, Jan-Thomas mGEODAR—A Mobile Radar System for Detection and Monitoring of Gravitational Mass-Movements |
title | mGEODAR—A Mobile Radar System for Detection and Monitoring of Gravitational Mass-Movements |
title_full | mGEODAR—A Mobile Radar System for Detection and Monitoring of Gravitational Mass-Movements |
title_fullStr | mGEODAR—A Mobile Radar System for Detection and Monitoring of Gravitational Mass-Movements |
title_full_unstemmed | mGEODAR—A Mobile Radar System for Detection and Monitoring of Gravitational Mass-Movements |
title_short | mGEODAR—A Mobile Radar System for Detection and Monitoring of Gravitational Mass-Movements |
title_sort | mgeodar—a mobile radar system for detection and monitoring of gravitational mass-movements |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664914/ https://www.ncbi.nlm.nih.gov/pubmed/33182236 http://dx.doi.org/10.3390/s20216373 |
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