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1. Software defined radar based frequency modulated continuous wave GPR

   https://doi.org/10.1117/12.2586099  

   Fiske, Patrick; Huston, Dryver; Xia, Tian (April 2021, SPIE Defense + Commercial Sensing: Radar Sensor Technology XXV)

   Raynal, Ann M.; Ranney, Kenneth I. (Ed.)

   Frequency modulated continuous wave (FMCW) radar allows for a wide range of research applications. One primary use of this technology which is explored in this paper is the ground penetrating radar. To achieve high sensing performance, wide-band spectral reconstruction and sophisticated image reconstruction algorithm have been developed to overcome hardware limitations. Applications and future work include Synthetic Aperture Radar (SAR) imaging, innovative GPR, and unmanned aerial vehicle (UAV) radar systems. 

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2. 3-D SAR imaging for multistatic GPR

   https://doi.org/10.1117/12.2519430  

   Pereira, Mauricio; Zhang, Yu; Huston, Dryver; Xia, Tian; Dhar, Nibir K.; Dutta, Achyut K.; Babu, Sachidananda R. (May 2019, SPIE Defense + Commercial Sensing, 2019, Proceedings Volume 10980, Image Sensing Technologies: Materials, Devices, Systems, and Applications VI; 109801D (2019))

   Ground penetrating radar (GPR) is a remote geophysical sensing method that has been applied in the localization of underground utilities, bridge deck survey, localization of landmines, mapping of terrain for aid in driverless cars, etc. Multistatic GPR can deliver a faster survey, wider spatial coverage, and multiple viewpoints of the subsurface. However, because of the transmit and receive antennas spatial offset, formation of 3D GPR image by simple stacking of the acquired A-scans is inaccurate. Also, averaging of different receivers data may lead to destructive interference of back-scattered waves due to different time delays implied by the spatial offset, so averaging does not lead to higher SNR in general. Furthermore, the energy back-scattered by scatter points are spread in hyperbolas in the GPR raw data. Migration or imaging algorithms are employed to increase SNR by focusing the hyperbolas. This focusing process also leads to better accuracy in target localization. In this paper, a computationally efficient synthetic aperture radar (SAR) imaging algorithm that properly integrates multistatic GPR data in both ground and air-coupled cases is presented. The algorithm is successfully applied on two synthetic datasets. 

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3. Ground Penetrating Radar Investigation of Late Pleistocene Shorelines of Pluvial Lake Clover, Elko County, Nevada, USA

   https://doi.org/10.3390/quat3010009  

   Munroe, Jeffrey S. (March 2020, Quaternary)

   Beach ridges constructed by pluvial Lake Clover in Elko County, Nevada during the Late Pleistocene were investigated with ground-penetrating radar (GPR). The primary objective was to document the internal architecture of these shorelines and to evaluate whether they were constructed during lake rise or fall. GPR data were collected with a ground-coupled 400-Mhz antenna and SIR-3000 controller. To constrain the morphology of the ridges, detailed topographic surveys were collected with a Topcon GTS-235W total station referenced to a second class 0 vertical survey point. GPR transects crossed the beach ridge built by Lake Clover at its highstand of 1725 m, along with seven other ridges down to the lowest beach at 1712 m. An average dielectric permittivity of 5.0, typical for dry sand and gravel, was calculated from GPR surveys in the vicinity of hand-excavations that encountered prominent stratigraphic discontinuities at known depths. Assuming this value, consistent radar signals were returned to a depth of ~3 m. Beach ridges are resolvable as ~90 to 150-cm thick stratified packages of gravelly sand overlying a prominent lakeward-dipping reflector, interpreted as the pre-lake land surface. Many ridges contain a package of sediment resembling a buried berm at their core, typically offset in a landward direction from the geomorphic crest of the beach ridge. Sequences of lakeward-dipping reflectors are resolvable beneath the beach face of all ridges. No evidence was observed to indicate that beach ridges were submerged by higher water levels after their formation. Instead, the GPR data are consistent with a model of sequential ridge formation during a monotonic lake regression. 

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4. Inundated Vegetation Mapping Using SAR Data: A Comparison of Polarization Configurations of UAVSAR L-Band and Sentinel C-Band

   https://doi.org/10.3390/rs14246374  

   Salem, Abdella; Hashemi-Beni, Leila (December 2022, Remote Sensing)

   Flood events have become intense and more frequent due to heavy rainfall and hurricanes caused by global warming. Accurate floodwater extent maps are essential information sources for emergency management agencies and flood relief programs to direct their resources to the most affected areas. Synthetic Aperture Radar (SAR) data are superior to optical data for floodwater mapping, especially in vegetated areas and in forests that are adjacent to urban areas and critical infrastructures. Investigating floodwater mapping with various available SAR sensors and comparing their performance allows the identification of suitable SAR sensors that can be used to map inundated areas in different land covers, such as forests and vegetated areas. In this study, we investigated the performance of polarization configurations for flood boundary delineation in vegetated and open areas derived from Sentinel1b, C-band, and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) L-band data collected during flood events resulting from Hurricane Florence in the eastern area of North Carolina. The datasets from the sensors for the flooding event collected on the same day and same study area were processed and classified for five landcover classes using a machine learning method—the Random Forest classification algorithm. We compared the classification results of linear, dual, and full polarizations of the SAR datasets. The L-band fully polarized data classification achieved the highest accuracy for flood mapping as the decomposition of fully polarized SAR data allows land cover features to be identified based on their scattering mechanisms. 

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5. Joint inversion of full-waveform ground-penetrating radar and electrical resistivity data — Part 2: Enhancing low frequencies with the envelope transform and cross gradients

   https://doi.org/10.1190/geo2019-0755.1  

   Domenzain, Diego; Bradford, John; Mead, Jodi (November 2020, GEOPHYSICS)

   Recovering material properties of the subsurface using ground-penetrating radar (GPR) data of finite bandwidth with missing low frequencies and in the presence of strong attenuation is a challenging problem. We have adopted three nonlinear inverse methods for recovering electrical conductivity and permittivity of the subsurface by joining GPR multioffset and electrical resistivity (ER) data acquired at the surface. All of the methods use ER data to constrain the low spatial frequency of the conductivity solution. The first method uses the envelope of the GPR data to exploit low-frequency content in full-waveform inversion and does not assume structural similarities of the material properties. The second method uses cross gradients to manage weak amplitudes in the GPR data by assuming structural similarities between permittivity and conductivity. The third method uses the envelope of the GPR data and the cross gradient of the model parameters. By joining ER and GPR data, exploiting low-frequency content in the GPR data, and assuming structural similarities between the electrical permittivity and conductivity, we are able to recover subsurface parameters in regions where the GPR data have a signal-to-noise ratio close to one. 

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