Polarimetric Ground Penetrating Radar Research Articles

Riemannian Quaternion Self-Organizing Map to Overcome Degree-of-Polarization Error in Polarimetric Ground-Penetrating Radar

Riemannian Quaternion Self-Organizing Map to Overcome Degree-of-Polarization Error in Polarimetric Ground-Penetrating Radar

Improved Detection of Buried Elongated Targets by Dual-Polarization GPR

Ground-penetrating radar (GPR) has been widely applied to the detection and delineation of buried targets in the subsurface. Compared with conventional single-channel GPR, polarimetric GPR has been proven to possess an improved ability to detect and characterize an elongated object in the subsurface. This letter proves that the scattering signals from a cylinder in two orthogonal polarization channels have a phase difference of about 90° when its diameter-to-wavelength ratio is about 0.05–0.33. Consequently, a polarization-difference imaging method, which shifts the VV component by −90° and subtracts it from the HH component, is proposed for the improved detection and imaging of a subsurface elongated object. Its effectiveness is verified by numerical, laboratory, and field tests on buried rebars and pipes. The signal-to-clutter ratios of the reconstructed GPR images can be improved by up to 4.5 dB by considering the phase difference between the dual-polarization components.

Automatic subsurface unexploded ordnance detection using a wideband full-polarization ground penetrating radar and entropy-based polarimetric signatures

An automatic buried unexploded ordnance (UXO) classification methodology based on the H-α entropy-based polarimetric features extracted from wideband (50–600 MHz) fully polarimetric ground penetrating radar (GPR) data is presented. This method first established a background H-α feature of the whole test site for determining the classification boundary of random and isotropic scatters. Then UXO-like elongated targets are detected by the presence of sufficient H-α feature appearing in the linear scattering classification zone. The detail processing and detection procedure will be discussed. The performance of the proposed UXO classifier will be evaluated using receiver operating characteristic (ROC) curve based actual field data collected at the US government Fort Ord UXO test site setup for evaluating different UXO detection technologies.

Polarimetric Chaotic Ground Penetrating Radar for Underground Pipes Detection

A polarimetric chaotic ground penetrating radar (GPR) is proposed to improve the detection accuracy of underground pipes. In this radar system, the chaotic signal is used as the probe signal and the multi-polarization detection mode is employed to gather the GPR data. Furthermore, the laplacian pyramid algorithm is applied to fuse multi-polarization components. The simulations demonstrate that by using the polarization chaotic GPR, the pipe responses are enhanced and their shape and distribution can be accurately obtained. Here, the information entropy, average gradient, spatial frequency, and standard deviation are introduced to quantitatively evaluate the imaging results. The corresponding experiment is consistent with the simulation. Additionally, to verify the performance of the polarimetric chaotic GPR, we compare the polarimetric chaotic GPR with the polarimetric stepped frequency continuous wave GPR. The experimental results show that the proposed radar improves the detection accuracy and enlarges the detection range.

Calibration of Interface Induced Polarization for Full Polarimetric Ground Penetrating Radar

The traditional ground penetrating radar (GPR) uses only one type of antenna for data acquisition, and only obtains single polarization data of targets. It can not fully describe the various properties of the target. Full polarimetric GPR is a new technology that uses four different polarization antennas to measure the target and can receive electromagnetic waves of different polarized directions to describe the polarization effect of targets. However, when the plane electromagnetic wave propagates through the ground surface, the polarized direction will rotate, namely interface induced polarization (IIP), which results in the complex interference embedded in the full polarimetric GPR data. In this research, firstly we discuss the generation of the IIP; subsequently how the IIP affect the full polarimetric GPR data is derived; finally the calibration formula is proposed and is applied to the GPR data processing.

Compact Dual-Polarized Vivaldi Antenna with High Gain and High Polarization Purity for GPR Applications

A compact ultra-wideband dual-polarized Vivaldi antenna is proposed for full polarimetric ground-penetrating radar (GPR) applications. A shared-aperture configuration comprising four Vivaldi elements for orthogonal polarizations is designed to reduce the low-end operating frequency and improve the port isolation with a compact antenna size. The directivity of the antenna is enhanced by the oblique position of the radiators and the implementation of a square loop reflector. Experimental results demonstrate that the antenna has very good impedance matching, port isolation, and dual-polarized radiation performance, with low dispersion characteristics across band of interest from 0.4 GHz to 3.0 GHz. GPR measurements with the designed antenna show that the antenna maintains good detection capability even for objects buried in a highly conductive soil.

An Unbalanced Sinuous Antenna for Near-Surface Polarimetric Ground-Penetrating Radar

Sinuous antennas are capable of producing ultra-wideband radiation with polarization diversity. This capability makes the sinuous antenna an attractive candidate for UWB polarimetric radar applications. Additionally, the ability of the sinuous antenna to be implemented as a planar structure makes it a good fit for close-in sensing applications such as ground-penetrating radar (GPR). In this work, each arm of a four-port sinuous antenna is operated independently to achieve a quasi-monostatic antenna system capable of polarimetry while separating transmit and receive channels-which is often desirable in GPR systems. The quasi-monostatic configuration of the sinuous antenna reduces system size as well as prevents extreme bistatic angles, which may significantly reduce sensitivity when attempting to detect near-surface targets. A prototype four-port sinuous antenna is fabricated and integrated into a GPR testbed. The polarimetric data obtained with the antenna is then used to distinguish between buried target symmetries.

Application of Polarimetric Features and Support Vector Machines for Classification of Improvised Explosive Devices

In this letter, we present a binary classification problem of improvised explosive devices, where true and false target features are taken from polarimetric ground-penetrating radar (GPR) signals. The radar measurements are carried out in laboratory and field scenarios by using dual-polarized Vivaldi antennas and ultrawideband multiple-input-multiple-output GPR (MIMO-GPR) systems in the frequency range from 0.8 to 5 GHz. Recursive algorithms, recursive least square, and linear predictive coding are used for clutter removal. To extract targets features of polarimetric measurements, eight data-processing methods are assembled, combining clutter removal algorithms, time-frequency transformations, and singular value decomposition. Moreover, for every method, 13 target feature vectors are constructed. Each vector is used to train and test a support vector machine algorithm for the classification problem. Classification results are validated by using leave-two-out cross-validation. Accuracy of 87.02% and a false positive rate of 10.53% in the best classifier were obtained.

Compensation of Dispersion in Sinuous Antennas for Polarimetric Ground Penetrating Radar Applications

In order to improve the accuracy of subsurface target classification with ground penetrating radar (GPR) systems, it is desired to transmit and receive ultra-wide band pulses with varying combinations of polarization (a technique referred to as polarimetry). The sinuous antenna exhibits such desirable properties as ultra-wide bandwidth, polarization diversity, and low-profile form factor, making it an excellent candidate for the radiating element of such systems. However, sinuous antennas are dispersive since the active region moves with frequency along the structure, resulting in the distortion of radiated pulses. This distortion may be compensated in signal processing with accurately simulated or measured antenna phase information. However, in a practical GPR, the antenna performance may deviate from that simulated, accurate measurements may be impractical, and/or the dielectric loading of the environment may cause deviations. In such cases, it may be desirable to employ a simple dispersion model based on antenna design parameters which may be optimized in situ. This paper explores the dispersive properties of the sinuous antenna and presents a simple, adjustable, model that may be used to correct dispersed pulses. The dispersion model is successfully applied to both simulated and measured scenarios, thereby enabling the use of sinuous antennas in polarimetric GPR applications.

Hybrid Polarimetric GPR Calibration and Elongated Object Orientation Estimation

Ground penetrating radar (GPR) has been widely applied to the detection of subsurface elongated targets, such as underground pipes, concrete rebars, and subsurface fractures. The orientation angle of a subsurface elongated target can hardly be delineated by a commercial single-polarization GPR system. In this paper, a hybrid dual-polarimetric GPR system, which consists of a circularly polarized transmitting antenna and two linearly polarized receiving antenna, is employed to detect buried elongated objects. A polarimetric calibration experiment using a gridded trihedral is carried out to correct the imbalances and cross talk between the two receiving channels. A full-polarimetric scattering matrix is extracted from the double-channel GPR signals reflected from a buried elongated object. An improved Alford rotation method is proposed to estimate the orientation angle of the elongated object from the extracted scattering matrix, and its accuracy is validated by a numerical test. A laboratory experiment was further conducted to detect five metal rebar buried in dry sand at different orientation angle relative to the GPR scan direction. The maximum relative error of the estimated angles of the buried rebars in the migrated GPR images is less than 5%. It is concluded that radar polarimetry can provide not only richer information than single-polarization GPR, but also a reliable approach for orientation estimation of a subsurface elongated object.

Particle Center Supported Plane for Subsurface Target Classification based on Full Polarimetric Ground Penetrating Radar

The subsurface target classification of ground penetrating radar (GPR) is a popular topic in the field of geophysics. Among the existing classification methods, geometrical features and polarimetric attributes of targets are primarily used. As polarimetric attributes contain more information of targets, polarimetric decomposition methods, such as H-Alpha decomposition, have been developed for target classification of GPR in recent years. However, the classification template used in H-Alpha classification is preset depending on the experience of synthetic aperture radar (SAR); therefore, it may not be suitable for GPR. Moreover, many existing classification methods require excessive human operation, particularly when outliers exist in the sample (the data set containing the features of targets); therefore, they are not efficient or intelligent. We herein propose a new machine learning method based on sample centers, i.e., particle center supported plane (PCSP). The sample center is defined as the point with the smallest sum of distances from all points in the same sample, which is considered as a better representation of the sample without significant effect of the outliers. In this proposed method, particle swarm optimization (PSO) is performed to obtain the sample centers; the new criterion for subsurface target classification is achieved. We applied this algorithm to full polarimetric GPR data measured in the laboratory and outdoors. The results indicate that, comparing with support vector machine (SVM) and classical H-Alpha classification, this new method is more efficient and the accuracy is relatively high.

Study of time-reversal-based signal processing applied to polarimetric GPR detection of elongated targets

Ground penetrating radar (GPR) is a useful sensing modality for mapping and identification of underground infrastructure networks, such as metal and concrete pipes (gas, water or sewer), phone conduits or cables, and other buried objects. Due to the polarization-dependent response of typical targets, it is of interest to investigate the optimum antenna arrangement and/or combination of arrangements that maximize the detection and classification capabilities of polarimetric GPR imaging systems. Here, we provide a preliminary study of time-reversal-based techniques applied to target detection by GPR utilizing different relative orientations of linear-polarized antenna elements (with respect to each other, as well as to the targets). We modeled three different pipe materials (metallic, plastic and concrete) and GPR systems operating at center frequencies of 100MHz and 200MHz. Full-wave numerical simulations are adopted to account for mutual coupling between targets. This type of assessment study may contribute to the improvement of GPR data interpretation of infrastructure networks in urban area surveys and in other engineering studies.

Application of Freeman decomposition to full polarimetric GPR for improving subsurface target classification

Migration technique can reconstruct the subsurface target imaging from record ground penetrating radar (GPR) data. Depending on the reconstructed imaging, we possibly distinguish subsurface target by the geometrical feature. But some different targets have similar reconstructed imaging, which will confuse us. Freeman decomposition is a technique for fitting a three-component scattering mechanism model to polarimetric synthetic aperture radar observations, which is successfully used in the classification of terrain objects. This paper applies the model-based Freeman decomposition to full polarimetric GPR data to improve the subsurface target classification. We use a full polarimetric GPR, which is constructed in laboratory with three types of antenna combinations, HH, VV and VH combinations, to acquire experiment data sets for testing the method. Metallic plate, ball, dihedral and volume scatter with many branches, are buried in the homogenous dry sand under flat ground surface, and three dimensional data sets are acquired above each buried target. After signal processing, we obtained subsurface target imaging by migration and color-coded polarimetric information by Freeman decomposition. Results showed that it can improve the classification capability of GPR for the subsurface target to use both the geometrical feature and polarimetric information.

Combination of H-Alpha Decomposition and Migration for Enhancing Subsurface Target Classification of GPR

Polarimetric technology has been one of the most important advances in microwave remote sensing during recent decades. H-alpha decomposition, which is a type of polarimetric analysis technique, has been common for terrain and land-use classification in polarimetric synthetic aperture radar. However, the technique has been less common in the ground penetrating radar (GPR) community. In this paper, we apply the H-alpha decomposition to analyze the surface GPR data to obtain polarimetric attributes for subsurface target classification. Also, by combining H-alpha decomposition and migration, we can obtain a subsurface H-alpha color-coded reconstructed target image, from which we can use both the polarimetric attributes and the geometrical features of the subsurface targets to enhance the ability of subsurface target classification of surface GPR. A 3-D full polarimetric GPR data set was acquired in a laboratory experiment, in which four targets, a scatterer with many branches, a ball, a plate, and a dihedral scatter, were buried in dry sand under flat ground surface, and used to test these techniques. As results, we obtained the subsurface H-alpha distribution and classified the subsurface targets. Also, we derived a subsurface H-alpha color-coded reconstructed target image and identified all four targets in the laboratory experiment.

LAND-BURIED OBJECT DETECTION AND TARGET-SHAPE RECOGNITION IN LOSSY AND DISPERSIVE SOIL

In this paper, a simulation of ground penetrating radar \GPR system on lossy and dispersive soil is investigated. The capability of the GPR system to detect buried targets is examined by evaluating and comparing the electromagnetic coupling between the transmitting and receiving antennas in two cases: (i) when the system is placed over an empty ground and (ii) when it is placed over a ground inside which a practical target is buried at a proper depth. Simulation software based on the flnite difierence time domain \XFDTD is used for the electromagnetic simulations. The results concerning the coupling between the transmitting and receiving antennas are presented considering various practical parameters such as the operating frequency, the electric properties of the ground soil and the buried target, and the location at which the receiving element is placed. It is shown that the target detectability is strongly dependent on all of the above parameters. Also, the capability of target shape extraction and recognition are demonstrated through polarimetric ground penetrating radar.

Compressional and EM wave velocity anisotropy in a temperate glacier due to basal crevasses, and implications for water content estimation

AbstractWe have conducted a series of experiments designed to investigate elastic and electromagnetic (EM) velocity anisotropy associated with a preferentially aligned fracture system on a temperate valley glacier in south-central Alaska, USA. Measurements include a three-dimensional compressional wave (P-wave) seismic reflection survey conducted over a 300 m x 300 m survey patch, with uniform source grid and static checkerboard receiver pattern. Additionally, we acquired a multi-azimuth, multi-offset, polarimetric ground-penetrating radar (GPR) reflection experiment in a wagon-wheel geometry with 94° of azimuthal coverage. Results show azimuthal variation in the P-wave normal-moveout velocity of >3% (3765 and 3630 m s–1 in the fast and slow directions respectively) and difference of nearly 5% between the fast (0.164 m ns–1) and slow (0.156 m ns–1) EM velocities. Fracture orientations estimated from the GPR and seismic velocity data are consistent and indicate a preferred fracture orientation that is 30-45° oblique to glacier flow; these measurements agree with borehole observations. Anisotropic analysis of the polarimetric data gives a single volumetric water content estimate of 0.73 ±0.11%. We conclude that meaningful estimates of physical properties in glaciers based on EM or seismic velocity measurements require collecting data such that the presence of anisotropy can be evaluated and an anisotropic analysis employed when necessary.

Calibration With High-Order Terms of Polarimetric GPR

To provide meaningful data, polarimetric ground penetrating radar (GPR) requires accurate calibration of channel imbalance and crosstalk not only in the amplitude term but also in the phase term. Currently, calibration techniques usually ignore higher-order terms to simplify equations. These techniques, though very easy to perform, provide less accurate calibration results for the crosstalk. To improve the accuracy of calibration, we have derived a new mathematical formulation to calibrate a polarimetric GPR system. We measured several scattering matrices to obtain the necessary calibration parameters. The calibration technique was tested from measurements conducted on a 22.5° oriented dihedral corner reflector from 1 to 6 GHz with a step of 0.1 GHz. The calibrated results are found to be consistent with the theoretically values, especially for the crosstalk.

3D polarimetric GPR coherency attributes and full-waveform inversion of transmission data for characterizing fractured rock

Ground-penetrating radar (GPR) can detect and describe fractures to help us characterize fractured rock formations. A fracture alters the incident waveform, or wave shape, of a GPR signal through constructive and destructive interference, depending on the aperture, fill, and orientation of the fracture. Because the electromagnetic (EM) waves of GPR are vectorial, features exhibiting strong directionality can change the state of polarization of the incident field. GPR methods that focus on changes in waveform or polarization can improve detection and discrimination of fractures within rock bodies. An algorithm based on coherency, a seismic attribute that delineates discontinuities in wavelet shape, is developed for polarimetric GPR. It uses the largest eigenvalue of the time-domain scattering matrix when calculating coherence. This algorithm is sensitive to wave shape and is unbiased by the polarization of GPR antennas. Polarimetric coherency works better than scalar coherency in removing the effects of polarization on field data collected from a fractured limestone plot used for hydrologic experimentation. Another method, for time-domain full-waveform inversion of transmission data, quantitatively determines fracture aperture and EM properties of fill, based on a thin-layer model. Inversion results from field data show consistency with the location of fractures from reflection data. These two methods offer better fracture-detection capability and quantitative information on fracture aperture, dielectric permittivity, and electrical conductivity of the fill than traditional GPR imaging and scalar-coherency attributes.

Evaluation of Van Khan Tooril’s castle, an archaeological site in Mongolia, by Ground Penetrating Radar

We report an implementation of the Ground Penetrating Radar (GPR) survey at a site that corresponds to a ruined castle. The objective of the survey was to characterise buried archaeological structures such as walls and tiles in Van Khan Tooril’s Ruin, Mongolia, by 2D and 3D GPR techniques. GPR datasets were acquired in an area 10 m by 9 m, with 10 cm line spacing. Two datasets were collected, using GPR with 500 MHz and 800 MHz frequency antennas. In this paper, we report the use of instantaneous parameters to detect archaeological targets such as tile, brick, and masonry by polarimetric GPR. Radar polarimetry is an advanced technology for extraction of target scattering characteristics. It gives us much more information about the size, shape, orientation, and surface condition of radar targets.We focused our interpretation on the strongest reflections. The image is enhanced by the use of instantaneous parameters. Judging by the shape and the width of the reflections, it is clear that moderate to high intensity response in instantaneous amplitude corresponds to brick and tiles. The instantaneous phase map gave information about the location of the targets, which appeared as discontinuities in the signal. In order to increase our ability to interpret these archaeological targets, we compared the GPR datasets acquired in two orthogonal survey directions. A good correlation is observed for the alignments of reflections when we compare the two datasets. However, more reflections appear in the north-south survey direction than in the west-east direction. This is due to the electric field orientation, which is in the horizontal plane for north-south survey directions and the horizontally polarised component of the backscattered high energy is recorded.

Subsurface structures detection by combining L-band polarimetric SAR and GPR data: example of the Pyla Dune (France)

The authors investigate the penetration capabilities of microwaves, particularly at L-band, for the mapping of subsurface heterogeneities such as lithology variations, moisture or sedimentary structures. The experiment site, the Pyla Dune, is a bare sandy area allowing high signal penetration and presenting large subsurface structures (paleosoils) at varying depths. Several radar data sets over this area are available. A polarimetric analysis of airborne synthetic aperture radar (SAR) data as web as the ground penetrating radar (GPR) sounding experiment show that subsurface scattering occurs at several places. The SAR penetration depth is estimated by inverting a scattering model for which the subsurface structure geometric and dielectric properties are determined by the GPR data analysis. These results suggest that airborne radar systems in a lower frequency range (P-band) should be able to detect subsurface moisture down to several meters, leading to innovative Earth observation systems for hydrogeology in arid regions.