Research

21 pages, 12274 KiB

Open AccessArticle

Characterization of Antenna Radiation Pattern and Penetration Depth in Ground Penetrating Radar Field Missions

by Pavel Morozov, Fedor Morozov, Maxim Lazarev, Leonid Bogolyubov and Alexei Popov

Remote Sens. 2023, 15(23), 5452; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15235452 - 22 Nov 2023

Viewed by 877

This article discusses the methods and results of assessing the angular resolution and sounding depth of enhanced-power ground penetration radars obtained during archaeological and geographical expeditionary works in various natural areas. Elongated local objects were used as test objects to evaluate the horizontal [...] Read more.

This article discusses the methods and results of assessing the angular resolution and sounding depth of enhanced-power ground penetration radars obtained during archaeological and geographical expeditionary works in various natural areas. Elongated local objects were used as test objects to evaluate the horizontal radiation pattern of the Loza–V georadar in the upper- and lower-half spaces. The depth of operation of the Loza–N low-frequency radar was estimated during a geophysical study of a unique natural object in the Siberian taiga. The variability of the GPR antenna radiation patterns in different materials (air, dry, or wet soils) confirms the necessity of quantitative measurements with controlled electrophysical parameters. Full article

(This article belongs to the Special Issue Microwave Imaging of Subsurface Objects in Applications for Engineering Technologies: Instruments and Methods)

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14 pages, 4326 KiB

Open AccessArticle

Common-Mode Clutter Filtering for the Problem of Sounding Multilayer Media Using Ground-Penetrating Radar

by Aleksandr Gorst, Ilya Tseplyaev, Aleksandr Eremeev, Rail Satarov, Sergey Shipilov, Ivan Fedyanin, Vitaly Khmelev, Dmitry Romanov and Roman Eremin

Remote Sens. 2023, 15(11), 2751; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15112751 - 25 May 2023

Viewed by 884

Abstract

Eliminating common-mode clutter in data is one of the key aspects of road sensing with GPR. Common-mode interference can occur as a result of multipath propagation of an electromagnetic signal when the reflected signal from the same object arrives at the receiver from [...] Read more.

Eliminating common-mode clutter in data is one of the key aspects of road sensing with GPR. Common-mode interference can occur as a result of multipath propagation of an electromagnetic signal when the reflected signal from the same object arrives at the receiver from different directions and with different delays. Similar phenomena also occur when using antennas raised above the surface due to multiple reflections between the air–surface interface and the antenna. These interferences can significantly distort the data received by the GPR and interfere with the accurate determination of the parameters of the roadway. Therefore, the elimination of common-mode clutter is an important task to improve the quality of the obtained results. In this paper, we consider a method for filtering common-mode clutter in the radar data of the multichannel GPR “Terrazond”, which were obtained by sounding a test section of a highway. The results obtained during filtering can then be used to determine the thickness of the pavement layers using approaches that take into account the signal delay determined by the amplitude jump, for example, the common point method or if the permittivity of each layer is known. The obtained thicknesses of pavement layers are compared with the results obtained during core drilling by the Russian Road Research Institute. Full article

(This article belongs to the Special Issue Microwave Imaging of Subsurface Objects in Applications for Engineering Technologies: Instruments and Methods)

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27 pages, 11197 KiB

Open AccessArticle

Characterization and Evaluation of Thaw-Slumping Using GPR Attributes in the Qinghai–Tibet Plateau

by Qing Wang, Xinyue Liu, Yupeng Shen and Meng Li

Remote Sens. 2023, 15(9), 2273; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15092273 - 25 Apr 2023

Viewed by 1128

Abstract

Due to the impact of climate warming and engineering construction, thaw-slumping has developed extensively along the Qinghai–Tibet Project Corridor. These landslide disasters not only destroy the fragile ecology of the Qinghai–Tibet Plateau but also threaten the security of the Qinghai–Tibet Project Corridor. Because [...] Read more.

Due to the impact of climate warming and engineering construction, thaw-slumping has developed extensively along the Qinghai–Tibet Project Corridor. These landslide disasters not only destroy the fragile ecology of the Qinghai–Tibet Plateau but also threaten the security of the Qinghai–Tibet Project Corridor. Because remote-sensing images lack imaging data inside the landslide body, and the excavation of boreholes has blindness and inefficiency, the ground-penetrating radar method with high efficiency and deep imaging has been developed and applied in the detection and treatment of thaw-slumping. To more accurately divide the soil-layered structure of the thaw-slumping body and obtain the key elements of the thaw-slumping such as temperature change trend and relative water content, we propose the use of amplitude event axis tracking and amplitude energy attenuation calculation to divide the fine layering of the thaw-slumping body. In addition, based on layer division, we introduce two attribute parameters to participate in the calculation of relative water content. These two attribute parameters are the weighted average frequency attribute, which reflects the temperature change trend, and the sweetness attribute, which reflects the change in the physical properties of the underground medium. The calculated 3D profile and time slice of the relative water content comprehensively show the change characteristics and enrichment area of the internal relative water content of the thaw-slumping. These methods and results are valuable for the characterization, evaluation, and treatment of thaw-slumping. Full article

(This article belongs to the Special Issue Microwave Imaging of Subsurface Objects in Applications for Engineering Technologies: Instruments and Methods)

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37 pages, 20131 KiB

Open AccessArticle

Implementation of an Artificial Intelligence Approach to GPR Systems for Landmine Detection

by Oleksandr A. Pryshchenko, Vadym Plakhtii, Oleksandr M. Dumin, Gennadiy P. Pochanin, Vadym P. Ruban, Lorenzo Capineri and Fronefield Crawford

Remote Sens. 2022, 14(17), 4421; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14174421 - 05 Sep 2022

Cited by 10 | Viewed by 2994

Abstract

Artificial Neural Network (ANN) approaches are applied to detect and determine the object class using a special set of the UltraWideBand (UWB) pulse Ground Penetrating Radar (GPR) sounding results. It used the results of GPR sounding with the antenna system, consisting of one [...] Read more.

Artificial Neural Network (ANN) approaches are applied to detect and determine the object class using a special set of the UltraWideBand (UWB) pulse Ground Penetrating Radar (GPR) sounding results. It used the results of GPR sounding with the antenna system, consisting of one radiator and four receiving antennas located around the transmitting antenna. The presence of four receiving antennas and, accordingly, the signals received from four spatially separated positions of the antennas provide a collection of signals received after reflection from an object at different angles and, due to this, to determine the location of the object in a coordinate system, connected to the antenna. We considered the sums and differences of signals received by two of the four antennas in six possible combinations: (1 and 2, 1 and 3, 2 and 3, 1 and 4, etc.). These combinations were then stacked sequentially one by one into one long signal. Synthetic signals constructed in such a way contain many more notable differences and specific information about the class to which the object belongs as well as the location of the searched object compared to the signals obtained by an antenna system with just one radiating and one receiving antenna. It therefore increases the accuracy in determining the object’s coordinates and its classification. The pulse radiation, propagation, and scattering are numerically simulated by the finite difference time domain (FDTD) method. Results from the experiment on mine detection are used to examine ANN too. The set of signals from different objects having different distances from the GPR was used as a training and testing dataset for ANN. The training aims to recognize and classify the detected object as a landmine or other object and to determine its location. The influence of Gaussian noise added to the signals on noise immunity of ANN was investigated. The recognition results obtained by using an ANN ensemble are presented. The ensemble consists of fully connected and recurrent neural networks, gated recurrent units, and a long-short term memory network. The results of the recognition by all ANNs are processed by a meta network to provide a better quality of underground object classification. Full article

(This article belongs to the Special Issue Microwave Imaging of Subsurface Objects in Applications for Engineering Technologies: Instruments and Methods)

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19 pages, 24546 KiB

Open AccessArticle

Learning-Based Clutter Mitigation with Subspace Projection and Sparse Representation in Holographic Subsurface Radar Imaging

by Cheng Chen, Tao Liu, Yu Liu, Bosong Yang and Yi Su

Remote Sens. 2022, 14(3), 682; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14030682 - 31 Jan 2022

Cited by 5 | Viewed by 2116

Abstract

The holographic subsurface radar (HSR) is an effective remote sensing modality for surveying shallowly buried objects with high resolution images in plan-view. However, strong reflections from the rough surface and inhomogeneities obscure the detection of stationary targets response. In this paper, a learning-based [...] Read more.

The holographic subsurface radar (HSR) is an effective remote sensing modality for surveying shallowly buried objects with high resolution images in plan-view. However, strong reflections from the rough surface and inhomogeneities obscure the detection of stationary targets response. In this paper, a learning-based method is proposed to mitigate the clutter in HSR applications. The proposed method first decomposes the HSR image into raw clutter and target data using an adaptive subspace projection approach. Then, the autoencoder is applied to carry out unsupervised learning to extract the target features and mitigate the clutter. The sparse representation is also combined to further optimize the model and the alternating direction multiplier method (ADMM) is used to solve the optimization problem for precision and efficiency. Experiments using real data were conducted to demonstrate that the proposed method can effectively mitigate the strong clutter with the target preserved. The visual and quantitative results show that the proposed method achieves superior performance on suppressing clutter in HSR images compared with the widely used state-of-the-art clutter mitigation approaches. Full article

(This article belongs to the Special Issue Microwave Imaging of Subsurface Objects in Applications for Engineering Technologies: Instruments and Methods)

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Review

Jump to: Research, Other

28 pages, 7963 KiB

Open AccessReview

An Overview on Down-Looking UAV-Based GPR Systems

by Carlo Noviello, Gianluca Gennarelli, Giuseppe Esposito, Giovanni Ludeno, Giancarmine Fasano, Luigi Capozzoli, Francesco Soldovieri and Ilaria Catapano

Remote Sens. 2022, 14(14), 3245; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14143245 - 06 Jul 2022

Cited by 16 | Viewed by 4987

Abstract

Radar imaging from unmanned aerial vehicles (UAVs) is a dynamic research topic attracting huge interest due to its practical fallouts. In this context, this article provides a comprehensive review of the current state of the art and challenges related to UAV-based ground-penetrating radar [...] Read more.

Radar imaging from unmanned aerial vehicles (UAVs) is a dynamic research topic attracting huge interest due to its practical fallouts. In this context, this article provides a comprehensive review of the current state of the art and challenges related to UAV-based ground-penetrating radar (GPR) imaging systems. First, a description of the available prototypes is provided in terms of radar technology, UAV platforms, and navigation control devices. Afterward, the paper addresses the main issues affecting the performance of UAV-based GPR imaging systems. such as the control of the UAV platform during the flight to collect high-quality data, the necessity to provide accurate platform position information in terms of probing wavelength, and the mitigation of clutter and other electromagnetic disturbances. A description of the major applicative areas for UAV GPR systems is reported with the aim to show their potential. Furthermore, the main signal-processing approaches currently adopted are detailed and two experimental tests are also reported to prove the actual imaging capabilities. Finally, open challenges and future perspectives regarding this promising technology are discussed. Full article

(This article belongs to the Special Issue Microwave Imaging of Subsurface Objects in Applications for Engineering Technologies: Instruments and Methods)

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36 pages, 14017 KiB

Open AccessReview

Design and Applications of Multi-Frequency Holographic Subsurface Radar: Review and Case Histories

by Sergey I. Ivashov, Lorenzo Capineri, Timothy D. Bechtel, Vladimir V. Razevig, Masaharu Inagaki, Nikolay L. Gueorguiev and Ahmet Kizilay

Remote Sens. 2021, 13(17), 3487; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13173487 - 02 Sep 2021

Cited by 8 | Viewed by 3631

Abstract

Holographic subsurface radar (HSR) is not currently in widespread usage. This is due to a historical perspective in the ground-penetrating radar (GPR) community that the high attenuation of electromagnetic waves in most media of interest and the inability to apply time-varying gain to [...] Read more.

Holographic subsurface radar (HSR) is not currently in widespread usage. This is due to a historical perspective in the ground-penetrating radar (GPR) community that the high attenuation of electromagnetic waves in most media of interest and the inability to apply time-varying gain to the continuous-wave (CW) HSR signal preclude sufficient effective penetration depth. While it is true that the fundamental physics of HSR, with its use of a CW signal, does not allow amplification of later (i.e., deeper) arrivals in lossy media (as is possible with impulse subsurface radar (ISR)), HSR has distinct advantages. The most important of these is the ability to do shallow subsurface imaging with a resolution that is not possible with ISR. In addition, the design of an HSR system is simpler than for ISR due to the relatively low-tech transmitting and receiving antennae. This paper provides a review of the main principles of HSR through an optical analogy and describes possible algorithms for radar hologram reconstruction. We also present a review of the history of development of systems and applications of the RASCAN type, which is possibly the only commercially available holographic subsurface radar. Among the subsurface imaging and remote sensing applications considered are humanitarian demining, construction inspection, nondestructive testing of dielectric aerospace materials, surveys of historic architecture and artworks, paleontology, and security screening. Each application is illustrated with relevant data acquired in laboratory and/or field experiments. Full article

(This article belongs to the Special Issue Microwave Imaging of Subsurface Objects in Applications for Engineering Technologies: Instruments and Methods)

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Other

Jump to: Research, Review

17 pages, 11665 KiB

Open AccessTechnical Note

Methods and Algorithms of Subsurface Holographic Sounding

by A. V. Popov, A. E. Reznikov, A. I. Berkut, D. E. Edemsky, P. A. Morozov and I. V. Prokopovich

Remote Sens. 2022, 14(20), 5274; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14205274 - 21 Oct 2022

Viewed by 1266

Abstract

In our experiments, we develop and test portable multi-element receiver antenna arrays, electrically scanned in order to immediately obtain a recognizable image of subsurface objects. Two quadrature components of the radar return signal are processed with a Kirchhoff backward migration algorithm. Physical theory [...] Read more.

In our experiments, we develop and test portable multi-element receiver antenna arrays, electrically scanned in order to immediately obtain a recognizable image of subsurface objects. Two quadrature components of the radar return signal are processed with a Kirchhoff backward migration algorithm. Physical theory is used to assess the quality of the holographic image, and the synthetic aperture approach is developed and tested. The parabolic wave equation and Gaussian beam technique are used in order to take into account refraction effects and to suppress specular reflection from the air-ground interface. Laboratory and field tests confirmed the predicted device parameters. Full article

(This article belongs to the Special Issue Microwave Imaging of Subsurface Objects in Applications for Engineering Technologies: Instruments and Methods)

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14 pages, 3430 KiB

Open AccessTechnical Note

Near Surface Velocity Estimation Using GPR Data: Investigations by Numerical Simulation, and Experimental Approach with AVO Response

by Ibrar Iqbal, Xiong Bin, Gang Tian, Honghua Wang, Peng Sanxi, Yang Yang, Zahid Masood and Sun Hanwu

Remote Sens. 2021, 13(14), 2814; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13142814 - 17 Jul 2021

Cited by 8 | Viewed by 2503

Abstract

The velocity of near-surface materials is one of the most important for Ground-Penetrating Radar (GPR). In the study, we evaluate the options for determining the GPR velocity to measure the accuracy of velocity approximations from the acquired GPR data at an experimental site [...] Read more.

The velocity of near-surface materials is one of the most important for Ground-Penetrating Radar (GPR). In the study, we evaluate the options for determining the GPR velocity to measure the accuracy of velocity approximations from the acquired GPR data at an experimental site in Hangzhou, China. A vertical profile of interval velocities can be estimated from each common mid-point (CMP) gather using velocity spectrum analysis. Firstly, GPR data are acquired and analyzed using the popular method of hyperbola fitting which generated surprisingly high subsurface signal velocity estimates while, for the same profile, the Amplitude variation with offset (AVO) analysis of the GPR data (using the same hyperbola fitting method) generate a more reasonable subsurface signal velocity estimate. Several necessary processing steps are applied both for CMP and AVO analysis. Furthermore, experimental analysis is conducted on the same test site to get velocities of samples based on dielectric constant measurement during the drilling process. Synthetic velocities generated by AVO analysis are validated by the experimental velocities which confirmed the suitability of velocity interpretations. Full article

(This article belongs to the Special Issue Microwave Imaging of Subsurface Objects in Applications for Engineering Technologies: Instruments and Methods)

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