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The multilayer nature of airport pavement structures is susceptible to the generation of voids at the bonding parts of the structure, which is also called interlayer debonding. Observations have shown that the thickness of the resulting voids is usually at the scale of millimeters, which makes it difficult to inspect. The efficient and accurate characteristics of ground penetrating radar (GPR) make it suitable for large area inspections of airport pavement. In this study, a multistatic GPR system was used to inspect the interlayer debonding of a large area of an airport pavement. A special antenna arrangement can obtain common-midpoint (CMP) gathers during a common-offset survey. The presence of interlayer debonding affects the phase of the reflection signals, and the phase disturbance can be quantified by the wavelet transform. Therefore, we have developed an advanced approach that uses the average entropy of the wavelet transform parameters in CMP gathers to detect the interlayer debonding of airport pavement. The results demonstrate that the regions with high entropy correspond to regions where tiny voids exist. The new approach introduced in this study was then evaluated by a field-base experiment at an airport taxiway model. The results show that our approach can detect interlayer debonding of the pavement model accurately and efficiently. On-site coring results confirm the performance of our approach.

As a recognised non-destructive testing (NDT) tool, Ground Penetrating Radar (GPR) is becoming increasingly common in the field of environmental engineering [1]-[3]. GPR uses electromagnetic (EM) waves which travel at specific velocity determined by the permittivity of the material. With the development of new GPR signal processing methodologies, finding information on the physical properties of hidden targets has become a key target. Currently, only three types of approach could be applied for the quantitative estimation of permittivity from GPR data, i.e., hyperbola curve fitting, common middle point (CMP) velocity analysis and full-waveform inversion. However, the main challenges for the estimation of permittivity from GPR backscattered signals are to provide effective and accurate strategy for prediction.In this research, we used a dual-polarimetric GPR system to estimate the dielectric constant of targets. The system is equipped with two 2GHz antennas polarised perpendicularly each to one another (HH and VV). The dual polarisation enables deeper surveying, providing images of both shallow and deeper subsurface features. Polarimetry is a property of EM waves that generally refers to the orientation of the electric field vector, which plays here an important role as it allows either direct or parameterisation permittivity effects within the scattering problem in the remote sensing [4].The aim of this research is to provide a novel and more robust approach for dielectric constant prediction using a dual-polarimetric GPR system. To this extent, the relationship between the relative permittivity and the polarimetric alpha angle have been investigated based on data collected by a GPR system with dual-polarised antennas. The approach was then assessed by laboratory experiments where different moisture sand targets (simulating the effect of different relative permittivity targets) were measured. After signal processing, a clear relationship between the alpha angle and the relative permittivity was obtained, proving the viability of the proposed method. AcknowledgementsThe authors would like to express their sincere thanks and gratitude to the following trusts, charities, organisations and individuals for their generosity in supporting this project: Lord Faringdon Charitable Trust, The Schroder Foundation, Cazenove Charitable Trust, Ernest Cook Trust, Sir Henry Keswick, Ian Bond, P. F. Charitable Trust, Prospect Investment Management Limited, The Adrian Swire Charitable Trust, The John Swire 1989 Charitable Trust, The Sackler Trust, The Tanlaw Foundation, and The Wyfold Charitable Trust. References[1] Zou, L. et al., 2020. Mapping and Assessment of Tree Roots using Ground Penetrating Radar with Low-Cost GPS. Remote Sensing, vol.12, no.8, pp:1300.[2] Zou, L. et al., 2020. On the Use of Lateral Wave for the Interlayer Debonding Detecting in an Asphalt Airport Pavement Using a Multistatic GPR System. IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 6, pp. 4215-4224.[3] Zou, L. et al., 2021. Study on Wavelet Entropy for Airport Pavement Debonded Layer Inspection by using a Multi-Static GPR System. Geophysics, vol. 86, no. 3, pp. WB69-WB78.[4] J. Lee and E. Pottier, Polarimetric Imaging: From Basics to Applications, FL, Boca Raton: CRC Press, 2009.

In this work, a novel signal processing framework for polarimetric GPR measurements is presented for inspection of tree trunks decay. The framework combines a polarimetric noise filter and an arc-shaped diffraction imaging algorithm. The polarimetric noise filter can increase the signal-to-noise ratio (SNR) of B-scans caused by the bark and the high-loss propriety of the tree trunk based on a 3D Pauli feature vector of the Bragg scattering theory. The arc-shaped diffraction stacking and an imaging aperture are then designed to suppress the effects of the irregular shape of the tree trunk on the signal. The proposed detection scheme is successfully validated with real tree trunk measurements. The viability of the proposed processing framework is demonstrated by the high consistency between the results and the real-truth trunk\ud cross-sections.

Urbanisation often leads to the destruction of green areas in the urban environment. To this extent, urban trees help mitigating its detrimental effects, as well as offering a variety of socioeconomic and environmental benefits. The presence of root systems in built environments usually results in structural damage, as for example shrinkage of expansive soils due to water suction by roots, resulting in subsidence and fissures in foundations, or roots obstructing pipes and sewers and damaging roads and pavements.\ud Ground Penetrating Radar (GPR) has been extensively used in various areas of civil and environmental engineering. Research has focused on implementing 3D algorithms and investigating root density, and a recent experimental research examined the feasibility of a novel tree root assessing methodology, that processes GPR data both in time and frequency domains. The aim of this research is to improve upon the above-mentioned data processing algorithm, investigating the variation of the frequency spectrum of the GPR signal in urban tree root systems’ surveys by means of a Short-Time Fourier Transform (STFT). Results proved the viability of the methodology and paved the way to further developments for the investigation of urban trees’ root systems using GPR.

In this paper, an efficient and accurate imaging algorithm is presented for Ground-Based Synthetic Aperture Radar (GB-SAR) or other radar systems that could be formed by a physical or synthetic linear aperture. The imaging algorithm is based on the fractional Fourier transform for the azimuth compression. A mathematical framework is derived according to the projection of a sample reflectivity image onto the pseudopolar coordinate and its implementation was presented. With the data acquisition geometry and the pseudopolar imaging coordinate, the phase of a point target can be expressed as a quadratic phase exponential. It makes that only one-dimensional fractional Fourier transform is needed for the azimuth compression of the time domain backscatter data for the GB-SAR imaging problem. By further research, the optimal transformation order which represents the spatial frequency changes by the fractional Fourier transform was given subsequently. Taking advantage of this optimal representation, the proposed approach avoids the large calculation that occurs in the time domain back projection (TDBP). Comparing to the far-field pseudopolar format algorithm (FPFA), the accuracy of the proposed algorithm is much improved. Meanwhile, the proposed approach holds the almost same computational cost and complexity as the FPFA. The proposed approach keeps the advantages of the imaging quality of the TDBP and the computational cost of the FPFA that are two important aspects of the GB-SAR applications. Both the numerical simulation and the field GB-SAR experiment show that the algorithm is more suitable for the high precision GBSAR imaging, especially for the near-field.

In this paper, the applicability of ground-based synthetic aperture radar (GB-SAR) as an early warning system for landslide monitoring is discussed. The effectiveness of the differential in...

The integrity and flatness of airport pavement facilities are important to maintain safe operations of aircrafts. Even a small defect and resulting debris can cause catastrophic accidents and, therefore, anomalies must be accurately detected for the first time before major damage occurs. To this effect, it is necessary to develop a low-cost, efficient, and accurate inspection technology to detect the anomalies in airport concrete pavements. In recent years, non-destructive testing (NDT) methods have been widely used in airport pavement inspection and maintenance due to the provision of reliable and efficient information. Amongst the NDT techniques, GPR can provide optimal resolutions for different applications in civil engineering due to the ultra-wide frequency band configuration [1][2]. However, for the investigation of airport pavement facilities main challenges are how to extract information from the reflections by small anomalies [3][4].In this research, we used a MIMO GPR system to inspect the interlayer debonding in a large area of an airport pavement. A special set of antenna arrangements of the system can obtain common mid-point (CMP) gathers during a common offset survey simultaneously. The existence of interlayer debonding affects the phase of the reflection signals, and the phase disturbance can be quantified by wavelet transform. Therefore, an advanced approach that uses the average entropy of the wavelet transform parameters in a CMP gathers to detect the interlayer debonding in airport pavements is proposed.The aim of this research is to provide more significant and accurate information for airport pavement inspections using a MIMO GPR system. To this extent, the wavelet entropy analysis is applied to identify the interlayer debonding existed in the shallow region. The proposed approach was then evaluated by field tests on an airport taxiway. The results were validated by on-site coring and demonstrate that the regions with high entropy correspond to the regions where tiny voids occurred. The proposed method has proven potential to detect the interlayer debonding of the pavement model accurately and efficiently. References[1] Alani, A. M. et al., 2020. Reverse-Time Migration for Evaluating the Internal Structure of Tree-Trunks Using Ground-Penetrating Radar. NDT&E International, vol.115, pp:102294.[2] Zou, L. et al., 2020. Mapping and Assessment of Tree Roots using Ground Penetrating Radar with Low-Cost GPS. Remote Sensing, vol.12, no.8, pp:1300.[3] Zou, L. et al., 2020. On the Use of Lateral Wave for the Interlayer Debonding Detecting in an Asphalt Airport Pavement Using a Multistatic GPR System. IEEE Transaction on Geoscience and Remote Sensing, vol. 58, no. 6, pp. 4215-4224.[4] Zou, L. et al., 2021. Study on Wavelet Entropy for Airport Pavement Debonded Layer Inspection by using a Multi-Static GPR System. Geophysics, in press.

In this work, the novel imaging algorithm of synthetic aperture radar (SAR) system to be used in near-range based on fractional Fourier transform is presented. The algorithm projects the target reflectivity function onto pseudopolar coordinates and focuses along the short time through the fractional Fourier transform. The discrete format procedure for imaging near-range target is also introduced in this paper. The numerical simulation results show that the algorithm is more suitable for the high-precision synthetic aperture radar imaging in the near field.

The preservation of natural assets is nowadays an essential commitment. In this regard, root systems are endangered by fungal diseases which can undermine the health and stability of trees. Within this framework, ground penetrating radar (GPR) is emerging as a reliable non-destructive method for root investigation. A coherent GPR-based root-detection framework is presented in this paper. The proposed methodology is a multi-stage data analysis system that is applied to semi-circular measurements collected around the investigated tree. In the first step, the raw data are processed by applying several standard and advanced signal processing techniques in order to reduce noise-related information. In the second stage, the presence of any discontinuity element within the survey area is investigated by analysing the signal reflectivity. Then, a tracking algorithm aimed at identifying patterns compatible with tree roots is implemented. Finally, the mass density of roots is estimated by means of continuous functions in order to achieve a more realistic representation of the root paths and to identify their length in a continuous and more realistic domain. The method was validated in a case study in London (UK), where the root system of a real tree was surveyed using GPR and a soil test pit was excavated for validation purposes. Results support the feasibility of the data processing framework implemented in this study.

In this paper, a coherent framework for estimating the density and the distribution of roots using ground penetrating radar is presented. The proposed methodology is a multi-stage data processing scheme that is applied in semi-circular measurements collected concentrically around the investigated tree. The adopted processing methodology consists of three distinct and sequential steps. In the first step, the raw B-scans are subject to time-zero correction, zero-offset removal, time-varying gain and the singular value decomposition (SVD) filter. The SVD filter is used in order to effectively eliminate multiples and ringing noise from the B-Scans and increase the overall signal-to-clutter ratio. The second step consists of a tracking algorithm that aims at identifying patterns that resemble tree roots. In the last step, a continuous function is fitted to each root in order to effectively interpolate between points and subsequently estimate the density of the roots. This paper concludes with a case study on an urban tree at the Gunnersbury Park, London, United Kingdom. The top soil around the tree was excavated to 40 cm below the surface approximately in order to expose the tree root architecture. Then the exposed tree root system was used to compare the survey results for validity purposes and ultimately support the viability of the proposed data processing methods adopted in this investigation.

In this paper, we have presented a methodology combining ground penetrating radar (GPR) and a low-cost GPS receiver for three-dimensional detection of tree roots. This research aims to provide an effective and affordable testing tool to assess the root system of a number of trees. For this purpose, a low-cost GPS receiver was used, which recorded the approximate position of each GPR track, collected with a 500 MHz RAMAC shielded antenna. A dedicated post-processing methodology based on the precise position of the satellite data, satellite clock offsets data, and a local reference Global Navigation Satellite System (GNSS) Earth Observation Network System (GEONET) Station close to the survey site was developed. Firstly, the positioning information of local GEONET stations was used to filter out the errors caused by satellite position error, satellite clock offset, and ionosphere. In addition, the advanced Kalman filter was designed to minimise receiver offset and the multipath error, in order to obtain a high precision position of each GPR track. Kirchhoff migration considering near-field effect was used to identify the three-dimensional distribution of the root. In a later stage, a novel processing scheme was used to detect and clearly map the coarse roots of the investigated tree. A successful case study is proposed, which supports the following premise: the current scheme is an affordable and accurate mapping method of the root system architecture.

Use of advanced health monitoring strategies for bridges is essential to provide a comprehensive condition assessment of these structures and ensure their structural integrity. To this purpose, new technologies have been applied in recent years for both static and dynamic assessments offering unprecedented opportunities within the context of risk management and structural analysis. Among these, areal deformation measurement techniques from ground-based synthetic aperture radar (GB-SAR) sensors were successfully applied for continuous monitoring of dynamic and static displacements of bridges [1] [2]. However, a main limitation for the ground-based microwave interferometry is that, as a linear measurement technique, it is difficult to pinpoint the damage location and obtain accurate displacement time-series for bridges [3]. Moreover, it is known that vertical displacements are usually more relevant than horizontal displacements in the dynamic monitoring of bridges, and the GB-SAR interferometry can only provide the line-of-sight (LOS) displacement of the monitored bridge [4].In this research, we focus on remote monitoring of the dynamic displacement responses of bridges with a polarimetric GB-SAR system. To this purpose, various strategies were used to overcome the existing limitations of this technique. Results from the monitoring of a long-span metallic railway bridge and a reinforced concrete Shinkansen bridge are discussed.The aim of this research is to provide more comprehensive and accurate information for bridge health monitoring using a polarimetric sensor. To this extent, a polarimetric analysis was performed to identify the reflection from the side surface of the bridges. In addition, the information about the polarisation orientation angle and the local incidence angle were processed under the acquisition geometry to calculate the radar look angle. Therefore, the bridge deformation fields in the vertical direction were easily converted using the slant range distances and the corresponding maximum transient vertical deformation was transformed through the LOS deformation while a train passing the bridge. References[1] Monserrat, O. et al., 2014. A review of ground-based SAR Interferometry for deformation measurement. ISPRS Journal of Photogrammetry and Remote Sensing, pp. 40–48.[2] Pieraccini, M. et al., 2006. Dynamic monitoring of bridges using a high-speed coherent radar. IEEE Transaction Geoscience and Remote Sensing, pp. 3284–3288.[3] Sato M., Zou L., Nico G., 2017. Monitoring of Infrastructure by GB-SAR. IEICE technical report, pp. 11-16.[4] Sato M., Zou L., Nico G., Kikuta K., 2019. Displacement and Vibration Monitoring by GB-SAR. IEICE Transactions on Communications, pp.844-852.

Non-destructive testing (NDT) for health monitoring of trees is a suitable candidate for detecting signs of early decay [1]. Recent developments [2,3,4] have highlighted that ground-penetrating radar (GPR) has the potential to provide with a robust and accurate detection tool with minimum computational and operational requirements in the field. In particular, a processing framework is suggested in [2] that can effectively remove ringing noise and unwanted clutter. Subsequently, an arc length parameterisation is employed in order to utilise a wheel-measurement device to accurately position the measured traces. Lastly, two migration schemes; Kirchhoff and reverse-time migration, are successfully applied on numerical and laboratory data in [3]. In the current paper, the detection scheme described in [2,3] using reverse-time migration is tested in two case studies that involve diseased urban trees within the greater London area, UK (Kensington and Gunnersbury park). Both of the trees were cut down after the completion of the measurements and furthermore cut into several slices to get direct information with regards to their internal structure. The processing scheme described in [3,4] managed to adequately detect the internal decay present in both trees. The aforementioned case studies provide coherent evidences to support the premise that GPR is capable of detecting decay in diseased trunks and therefore has the potential to become an accurate and efficient diagnostic tool against emerging infectious diseases of trees. Acknowledgements The authors would like to express their sincere thanks and gratitude to the following trusts, charities, organizations and individuals for their generosity in supporting this project: Lord Faringdon Charitable Trust, The Schroder Foundation, Cazenove Charitable Trust, Ernest Cook, Sir Henry Keswick, Ian Bond, P. F. Charitable Trust, Prospect Investment Manage- ment Limited, The Adrian Swire Charitable Trust, The John Swire 1989 Charitable Trust, The Sackler Trust, The Tanlaw Foundation and The Wyfold Charitable Trust. This paper is dedicated to the memory of Jonathon West, a friend, a colleague, a forester, a conservationist and an environmentalist who died following an accident in the woodland that he loved. References[1] P. Niemz, D. Mannesm, ”Non-destructive testing of wood and wood-based materials,” J. Cult. Heritage, vol. 13, pp. S26-S34, 2012.[2] I. Giannakis, F. Tosti, L. Lantini and A. M. Alani, "Health Monitoring of Tree Trunks Using Ground Penetrating Radar," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 10, pp. 8317-8326, 2019.[3] I. Giannakis, F. Tosti, L. Lantini and A. M. Alani, "Diagnosing Emerging Infectious Diseases of Trees Using Ground Penetrating Radar," IEEE Transactions on Geoscience and Remote Sensing, Early Access, doi: 10.1109/TGRS.2019.2944070 [4] A. M. Alani, F. Soldovieri, I. Catapano, I. Giannakos, G. Gennarelli, L. Lantini, G. Ludeno and F. Tosti, “The Use of Ground Penetrating Radar and Microwave Tomography for the Detection of Decay and Cavities in Tree Trunks,” Remote Sensing, vol. 11, no. 18, 2019.

In this article, an atmospheric phase screen (APS) compensation algorithm for a near real-time ground-based interferometry synthetic aperture radar (GB-InSAR) over a mountainous area is investigated. A novel APS compensation scheme is proposed to compensate the fluctuated APS caused by a spatial 3-D inhomogeneous refractivity index distribution without any a priori knowledge of moving location. The proposed method simultaneously addresses to identify moving pixels by a criterion of absolute velocity estimated by the coherent pixels technique (CPT). The proposed method consists mainly of three steps: 1) the stratified APS compensation; 2) identification of moving pixel candidate; and 3) the residual APS [remained APS after 1)] compensation by Kriging interpolation. The steps mentioned above are iteratively applied in order to increase the accuracy of the whole process. In this framework, we develop the 2-D quadratic polynomial model of the refractivity index with respect to slant range and topographic height for modeling the stratified APS. Furthermore, a prediction of the residual APS is achieved by applying the intrinsic random function of order $k$ (IRF- $k$ ) Kriging interpolation, taking into account the nonstationarity of the residual APS. We evaluate the proposed method using zero-baseline GB-differential InSAR (GB-DInSAR) data over a mountainous area located in Minami-Aso, Kumamoto, Japan, through the near real-time post-landslide measurement campaign.

Modern socioeconomic factors such as global timber trade and international travelling have contributed to the rapid increase of Emerging Infectious Diseases (EIDs) of trees with devastating effects to the European forests and woodlands. To that extent, numerous non-destructive methodologies have been suggested as diagnostic tools in order to effectively monitor and maintain potential outbreaks. Ground-penetrating radar (GPR) is an appealing method for tree monitoring as it provides with a trivially deployable and efficient detection tool, suitable for large-scale forestry applications. Nonetheless, traditional GPR approaches are tuned for surface measurements and they are not compatible with the unique measurement configurations associated with forestry applications. Within that context, we present a novel-processing framework, which is capable of addressing features with irregular measurements on closed surfaces. A positioning method is described that exploits a wheel-measuring device in order to accurately associate each A-Scan with its corresponding coordinates. In addition, a processing pipeline is presented that aims at eliminating the ringing noise due to the layered nature of the trees. Lastly, a reverse-time migration is applied to the processed B-Scan in order to effectively map the reflectors present within the trunk. The suggested scheme is successfully tested in both numerical and real-field experiments, indicating the validity of the current approach.

Trees and woodlands are nowadays threatened by variety of aggressive diseases and fungal infections. As a result, internal decays in trees, can lead to the creation of cavities and large holes inside the trunks, which in turn can seriously undermine the stability and the integrity of the tree. In this regard, ground-penetrating radar (GPR) has recently proven to be an effective non-destructive testing (NDT) method, with the potential of providing information about the internal structure of trees. However, the particular shape of tree trunks prevents the use of traditional data processing techniques, and only limited information can be collected for tree health assessment purposes. This study shows the potential of GPR enhanced by a microwave tomography inversion approach in detecting tree cavities and hollows. A hollow tree was investigated by performing a set of circular GPR scans, and the internal structure of the trunk was reconstructed via tomographic imaging. The achieved results were validated by way of comparison with real sections cut from the tree and prove the validity of the proposed methodology in identifying the dimension and shape of cavities and hollows in tree trunks.

We propose a high-resolution velocity analysis method to estimate the electromagnetic wave propagation velocity in subsurface medium. The estimation is achieved by applying the l-1 norm regularized least-squares method to the conventional common-midpoint (CMP) velocity analysis algorithm. The proposed method can provide not only higher resolution than the conventional velocity analysis method, but can also be applied with a coarse sampling array system, such as our array ground penetrating radar YAKUMO, which returns eight CMP traces within a two meter width. The main purpose of this approach is for precise pavement inspection at shallow depths. We applied this method to both a simulated dataset and real data acquired by YAKUMO at a model airport taxiway to detect the slight velocity changes caused by millimeter-thin cracks filled with air or water within the 15 cm-thick asphalt pavement. In both cases slight velocity changes of about 0.005 m/ns can be detected, and the difference between air- and water-filled cracks can be distinguished. Also, this method is applied to a data acquired at airport taxi-way, the damaged parts are detected successfully and shows good agreement with the corning results. The results indicate that the proposed method is effective for pavement inspection, especially in the presence of thin cracks that cannot be seen directly with the reflected signal.

In this study, an anomalous atmospheric phase screen (APS) compensation in the frame of a ground-based differential synthetic aperture radar interferometry (GB-DInSAR) is investigated. The two improved methods are proposed and verified with GB-SAR data acquired at the mountain cliff exposed by a landslide. The first method adopts the piecewise multiple regression approach by assuming the inhomogeneity of the refractivity index distribution along the range direction. As for the second method, we apply nth order of two-dimensional (2D) polynomial with respect to slant range and topography height which enables the flexible fitting for the anomalous APS. In the second method, the cross-validation is employed to avoid both underfitting and overfitting problem. The applicability of both methods is validated with GB-DInSAR data which presents the anomalous APS. As a result, both methods yield significant reduction of the residual error compared to the conventional method.

To identify the slight spatial variability in the electromagnetic(EM) signal propagation velocity and thickness of an asphalt layer caused by the presence of thin cracks within the layer, a practical interferometric approach using the multistatic ground-penetrating radar system YAKUMO was introduced in this study. It was demonstrated that several parallel distributed common midpoint (CMP) datasets can be acquired at each position while moving the system in real time, which makes it possible to apply this method to large-scale inspections. the proposed method can provide much higher-resolution estimations of slight deviations in the velocity and thickness from their corresponding reference values in the undamaged asphalt through the comparison of two CMP datasets, and these deviations can be obtained analytically instead of graphically extracted from the velocity spectrum. In this work, a short-term monitoring dataset is acquired at an airport taxi-way model during it was damaged artificially. This dataset is analyzed with proposed method in order to recognize the conditions of damaged pavement at different stages. The results show that the performed method can indicate the damaged part at different stages. This method provides a novel way to inspect partially damaged pavement when the damage is difficult to observe using the reflected signal only.

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.

It is important to identify the thin cracks within the airport pavement layers. To achieve this goal, a practical interferometric approach using the Yakumo multistatic ground-penetrating radar system was developed to detect the slight variability in wave propagation velocity and/or thickness caused by the thin cracks. In comparison with the conventional common midpoint (CMP) velocity estimation method, the proposed method can provide much higher-resolution estimations of slight deviations in the velocity and thickness from their corresponding reference values in the undamaged asphalt through the comparison of two CMP datasets. These deviations can be obtained analytically instead of graphically extracted from the CMP velocity spectrum. The proposed approach was not only analyzed using the simulated datasets, but also practically demonstrated at both an experimental model site and an actual airport site. In the simulation tests, velocity deviations on the order of a few millimeters per nanosecond were detected, and the experimental results shows good agreement with the ground truth and coring samples. This method provides a novel way to inspect partially damaged pavement when the thin cracks are difficult to detect using the reflected signals.

In this paper, a new coherent scatterers selection in GB-SAR is presented. Instead of evaluating the temporal stability of the pixels, this approach interleaved along frequency direction to obtain sub-images from one dataset. Pixels satisfied low values of entropy along these sub-images have been selected as coherent scatterers. The performance of the proposed approach has been evaluated by real GB-SAR data acquired both in the urban and rural area, and the final coherent scatterers maps obtained by proposed approach are compared with conventional dispersion of amplitude approach. Both approachs selected almost identical coherent scatterers. But, coherent scatterers with short temporal characterized properties were selected by the proposed approach.

Polarimetric GPR requires accurate calibration of channel imbalance and crosstalk not only in the amplitude term but also in the phase term. Currently, there have some calibration techniques. Though these techniques are very easy to perform, they provide less accurate calibration results for the crosstalk. To improve on the accuracy of calibration, we have developed a mathematical formulation to calibrate polarimetric GPR data. We measured several scattering matrices to obtain the necessary calibration parameters. The calibration technique was tested from measurements conducted on dihedral corner reflector.

Generally GPR transmits and receives radio waves with a single polarization using two parallel antennas. But it is possible to improve the GPR ability of discrimination and imaging of subsurface targets by analyzing the backscattered wave with a variety of polarizations. So we are developing a full-polarimetric GPR system, including PC, network analyzer, rectangular coordinates robot, switch driver, and polarimetric antenna array. Polarimetric antenna array is used to transmit and receive both co-polarimetric and cross-polarimetric signals. Currently polarimetric GPR do not execute precise calibration. But good calibration can improve the classification ability of subsurface targets. So we introduced the calibration technique into the polarimetric GPR, and derived a calibration formula.

Fractured reservoir plays an important role in exploitation of the oil-gas recourses especially shale gas, at the same time the fractures have an important influence on the dams, bridges, highways and other builds. So fracture detection and its attribute evaluation is an important aim on study of exploration geophysics. Both electromagnetic wave and elastic wave have a good effect on fracture detection and its attribute evaluation. Joint exploration and inversion is an effective way to improve the accuracy of exploration. But we needs further study on the propagation response characteristics of electromagnetic wave and elastic wave. Physical simulation is an intuitionistic and effective method in study two kinds of wave-field propagation response characteristics in fractured media. So we carry out the combining electromagnetic wave and ultrasonic wave physical simulation experiment on fractured medium model. We have established a three-dimensional physical model with a series of tiny parallel fractures in the vertical. And we have explored this model using by ground penetrating radar, and collected electromagnetic sounding data of three-dimensional co-polarization and cross-polarization, and analysed polarization characteristics. At the same time we have explored this model using three-component transducer, and collected elastic wave data of three-dimensional, and analysed shear wave propagation characteristics. By making a study of the change of co-polarization and cross-polarization response amplitude values and the phenomenon of S-wave splitting in elastic wave, we can judge the direction and density of cracks and other properties in it. By study of the two kinds of wave-field physical simulation, we can lay a solid foundation for joint inversion of electromagnetic wave and ultrasonic wave in the future.