Sampling Frequency Fluctuations of the Sensors and Software SPIDAR Ground Penetrating Radar: Impact on Probing Passive Surface Acoustic Wave Delay Lines for Pollution Sensing

In the context of the subsurface pollutant detection using cooperative targets probed by ground penetrating RADAR (GPR), we assess the sampling frequency stability of the instrument as needed to make sure any time delay variation between echoes is associated with subsurface chemical detection and no...

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Bibliographic Details
Published inIEEE geoscience and remote sensing letters Vol. 19; pp. 1 - 5
Main Authors Rabus, D., Arapan, L., Pierre, T., Friedt, J.-M., Cherioux, F.
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:In the context of the subsurface pollutant detection using cooperative targets probed by ground penetrating RADAR (GPR), we assess the sampling frequency stability of the instrument as needed to make sure any time delay variation between echoes is associated with subsurface chemical detection and not with instrument drift. Thanks to surface acoustic wave (SAW) transducers designed as GPR cooperative targets, the sampling frequency of the sensors and Software SPIDAR GPR control unit is characterized for short- and long-term sampling rate stabilities. The long-term stability of the instrument is below the phase measurement noise of the SAW cooperative target. However, short-term (within each trace) phase fluctuations are observed, hinting at short-term stroboscopic delay synthesis artifacts. Having demonstrated the stability of the baseline, we demonstrate gas-phase pollutant detection in the subsurface environment using GPR interrogation of a SAW sensor functionalized with a dedicated coating for reacting with hydrogen sulfide. Finally, for onsite long-term monitoring, an embedded vector network analyzer is shown to exhibit sufficient stability and the targeted performance for this measurement by recovering the time-domain response through the inverse Fourier transform of the frequency swept characterization of the sensor.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2020.3048084