mGEODAR-A Mobile Radar System for Detection and Monitoring of Gravitational Mass-Movements.

mGEODAR-A Mobile Radar System for Detection and Monitoring of Gravitational Mass-Movements.
复制标题

DOI:
10.3390/s20216373
复制
发表时间:
2020-11-09
期刊:
Sensors (Basel, Switzerland)
影响因子:
--
通讯作者:
Fischer JT
Fischer JT
中科院分区:
其他
文献类型:
--
作者:
Köhler A;Lok LB;Felbermayr S;Peters N;Brennan PV;Fischer JT

文献摘要

参考文献

相似文献

雷达测量重力质量运动,如雪崩,已成为越来越重要的科学流动观测,实时检测和监测。独立的可见性是一个主要的优势,快速和可靠的检测这些事件,可实现的高分辨率成像证明是非常宝贵的科学测量的完整的流动演变。现有的雷达系统要么是低分辨率探测,要么是大型设备,永久安装在试验场。我们提出mGEODAR,一个移动的FMCW(调频连续波)雷达系统的高分辨率测量和低分辨率的重力质量运动检测和监测的目的,由于一个通用的频率生成方案。我们优化了不同频率设置的性能与环路电缆测量和显示的自由空间范围的灵敏度与数据的汽车作为移动点源。电缆测试的信噪比约为15 dB,汽车在检测和研究模式下的信噪比分别约为5 dB或10 dB。通过将低分辨率检测模式下的连续记录与高分辨率研究模式的实时触发相结合,我们预计mGEODAR能够快速响应不断变化的天气和雪况,实现基础设施安全和质量运动研究目的的自主测量活动。
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.
DOI: 10.1016/j.coldregions.2007.03.009
发表时间: 2007-11-01
影响因子: 4.1
作者:
Gauer, Peter;Kern, Martin;Schreiber, Helmut
通讯作者: Schreiber, Helmut
DOI: 10.1002/2017jf004375
发表时间: 2018-06-01
影响因子: 3.9
作者:
Kohler, A.;McElwaine, J. N.;Sovilla, B.
通讯作者: Sovilla, B.
DOI: 10.1364/osac.2.003576
发表时间: 2019-12-15
期刊: OSA CONTINUUM
影响因子: 1.6
作者:
Long, David A.;Reschovsky, Benjamin J.
通讯作者: Reschovsky, Benjamin J.
DOI: 10.3189/1985aog6-1-26-34
发表时间: 1985-01-01
影响因子: 2.9
作者:
SALM, B;GUBLER, H
通讯作者: GUBLER, H
DOI: 10.1121/1.4929619
发表时间: 2015-09-01
影响因子: 2.4
作者:
Taraldsen, Gunnar;Berge, Truls;Jonasson, Hans
通讯作者: Jonasson, Hans