Correlation of Ground Penetrating Radar Data with Geotechnical Prospect Profiles: Reduto Case Study, Belém-PA, Brazil

The study presented in this manuscript aimed to relate the sedimentary strata imaged by the ground penetrating radar(GPR)method through numerical modeling with the mapping of sedimentary strata acquired through geotechnical surveys.The study aimed to expose how obtaining subsoil information through noninvasive/destructive electromagnetic waves is beneficial,as they are reliable and less costly than drilling holes beyond what is necessary to have a subsurface mapping.In this sense,physical-geological modeling was carried out.The information on the type of sediments,acquired through simple recognition surveys carried out in the city of Belém-PA,helped to create a model of a sedimentary package with its respective intrinsic physical properties.The result shows that the GPR recovered with good vertical and horizontal resolution at the beginning and end of the layers of the sedimentary package studied,proving to be very effective for locating geotechnical sounding points and safely reducing costs.

Interpretation of Dune Genesis from Sedimentogical Data and Ground Penetrating Radar (GPR) Signatures: A Case Study from Ashirmata Dune Field, Mandvi Beach, Gujarat, India

The coastal dunes located near the Ashirmata region, south of Mandvi beach lies near the straight coast have been stud-ied by making use of sedimentological information and Ground Penetrating Radar (GPR) data. Sedimentological analy-sis reveals the NNW-SSE trending longitudinal dunes consists of well sorted fine sands with unimodal distribution pos-sibly formed by constant wind gust and also the point out to the origin of sediments from single source;mostly the sediments derived from Indus delta transported to beach by long shore drift and tidal waves, carried inland by local on-shore winds. The radargram confirms, the homogenous sand layers with paleosols at shallow depth slip faces are proba-bly formed due to extreme storm activity of Recent.

Ground Penetrating Radar(GPR) Applications in Hydrogeological Study of Aquifers

Ground penetrating radar is a noninvasive electromagnetic geophysical technique for subsurface exploration,characterization and monitoring.Ground penetrating radar is sometimes called georadar, ground probing radar,or subsurface radar,earth sounding radar / radar terrestre penetrant,Well Probing Radar,and Borehole Radar.The principles involved are similar to reflection seismology,except that electromagnetic energy is used instead of

Ground Penetrating Radar (GPR) Investigations for Architectural Heritage Preservation: The Case of Habib Sakakini Palace, Cairo, Egypt

A comprehensive Ground Penetration Radar (GPR) investigations and hazard assessment for the rehabilitation and strengthening of Habib Sakakini’s Palace in Cairo is presented herein, which is considered one of the most significant architectural heritage sites in Egypt. The palace located on an ancient water pond at the eastern side of Egyptian gulf besiding Sultan Bebris Al-Bondoqdary mosque is a place also called “Prince Qraja al-Turkumany pond”. That pond had been filled down by Habib Sakakini at 1892 to construct his famous palace in 1897. The integrated geophysical survey of the palace allowed the identification of several targets of potential archaeological and geotechnical engineering interest buried in fill and silty clay in the depth range between 100 - 700 cm. the methodological development focused on Multi-Fold (MF) Ground Penetrating Radar (GPR) imaging and subsurface characterization based on integrated velocity and attenuation analysis. Eight hundred sqm of Ground penetration Radar (GPR) profiling have been conducted to monitor the subsurface conditions. 600 meters are made in the surrounding area of the Palace and 200 sqm at the basement. The aim is to monitor the soil conditions beneath and around the Palace and to identify potential geological discontinuities, or the presence of faults and cavities. A suitable single and dual antenna are used (500 - 100 MHZ) is used to penetrate the desired depth of 7 meters (ASTM D6432). The GPR is used also detect the water table. At the building basement the GPR is used to identify the foundation thickness and soil-basement interface. As well as the inspection of cracks in some supporting columns, piers and masonry walls. The GPR also was used to investigate the floors and ceilings conditions and structural mapping. The results were validated by the geotechnical and structural surveys. All these results together with the seismic hazard analysis will be used for the complete analysis of the palace in the framework of the rehabilitation and strengthening works foreseen in a second stage.

Detection of the Possible Buried Archeological Targets Using the Geophysical Methods of Ground Penetrating Radar (GPR) and Self Potential (SP), Kom Ombo Temple, Aswan Governorate, Egypt

Kom Ombo temple is one of temples which were belted over high plateau close to the River Nile, near to Aswan in Egypt in the Greek-Roman period. The expected archaeological remains in the selected area are the hidden tunnels of the mummified crocodiles. The aim of the present work is to detect any of these tunnels by the application of the (GPR) and (SP) methods. The interpretation of the 10 GPR profiles revealed some locations of possible hidden tunnels. These locations show different contrasts and high amplitudes of the reflected signals, compared to the enclosing soil;also the scattering of the signals is higher than the bed layer in these locations, which may reveal the possible buried mummified crocodile tunnels in the study area. The depths of the possible targets range from 2.0 m to 2.5 m. The SP electric map shows that the study area possesses a range of about 135 mV of the potential differences between the measured stations. The positive response of the SP data is mainly concentrated at the central part of the study area. The relatively weak, negative SP anomalies may be related to moisture in the soil. The positive SP anomalies on the SP electric map display possible significant correlation between them and the inferred tunnel locations from the GPR data. The calculated depths from the SP profiles show significant agreement with that estimated from GPR data depths, which indicate that the SP electric method can be used as a successful tool in detecting buried archaeological remains in support of GPR.

GPR信号去噪的变分模态分解

为了进一步提高探地雷达(ground penetrating radar,GPR)数据的信噪比,压制由随机扰动引起的随机绕射能量,将二维变分模态分解(two-dimensional variational mode decomposition,2D-VMD)引入二维GPR数据的噪声压制处理中。首先,对GPR数据进行2D-VMD处理,并分析各阶本征模态函数(intrinsic mode function,IMF)分量及其对应的频率-波数域谱来确定雷达剖面中的各回波类型。然后,计算IMF分量与原始数据的互相关系数来确定信号模态和噪声模态,并对信号模态进行重构得到降噪后的数据。理论数据和实测数据测试表明,相比于传统的1D-VMD法,2D-VMD滤波后的含噪正演记录峰值信噪比由6.44 dB增加到7.72 dB;经2D-VMD降噪处理后的雷达剖面在保留有效信号的基础上,可以有效压制随机扰动带来的噪声,并且得到的雷达剖面同相轴连续性更好。

gprMax干扰消除方法优化隧道壁后空洞成像特征研究

为解决传统探地雷达图像处理方法在检测隧道衬砌钢筋影响下的壁后空洞时,二维模型不能有效描述空洞三维特征,存在计算效率低、计算精度不足的问题,综合运用平均消除法、指数增益法和时间零点校正法,结合雷达信号随双程窗口时间变化的特点,引入分段函数计算步骤,提出gprMax干扰消除方法,并验证该方法在正演模拟结果处理中的可行性。结合工程实际注浆情况和隧道壁后空洞的检测过程,采用基于时域有限差分法的gprMax软件设计隧道壁后注浆空洞的三维模型,采用gprMax干扰消除方法优化图像结果,对不同工况下的正演模拟图像成像特征进行分析。结果表明:1)gprMax干扰消除方法的正演模拟处理结果与室内混凝土板中圆形空洞结构模型试验的实测结果总体一致;2)水平测线中矩形空洞信号特征呈现出“凹”字形,垂直测线中矩形空洞信号特征呈现出类似直达波的特征,由空洞的三维特征图获取数据可计算得到空洞尺寸和埋深信息;3)gprMax干扰消除方法可以有效增强埋深较大处空洞的电磁信号强度。由研究结果可知,gprMax干扰消除方法在提高了隧道壁后空洞检测数据处理效率的同时保证了计算准确性和精度。

基于GPR探测的长江源地区冰川与冻土厚度研究

长江源地区的冰川变化揭示了青藏高原气候变化趋势。冰下地形探测作为冰川发育和运动过程研究的基础,对长江地区水土保持和淡水资源储量研究具有指导意义。长江科学院在长达10 a的江源科考基础上,分别于2022年、2023年采用探地雷达(GPR)技术对长江正源沱沱河发源地格拉丹东主峰的冰川厚度进行精准探测,并对查旦湿地冻土厚度上限进行了探测研究。结合多种冰川和冻土地质模型的GPR波场模拟结果,提高了GPR技术在长江源地区冰川和冻土探测的有效性和精准度。探测结果表明,格拉丹东主峰冰川厚度和查旦湿地冻土厚度上限均有不同程度降低,冰川厚度和冻土厚度上限观测是一个常年积累的结果,后续仍需持续进行观测,积累更多数据,分析变化趋势,以估算探测区域内冰储量,研究气候变化对冰川的影响效果。

基于HSP⁃GPR法的隧道三维超前地质预报技术及应用

隧道施工中,岩溶致灾构造容易引发岩溶涌突水、坍方、地表塌陷等地质灾害,严重威胁隧道施工安全。因此,进行超前地质预报对确保岩溶区域隧道施工安全至关重要。从岩溶隧道施工地质灾害、致灾构造及致灾模式为出发点,基于地震波法与电法联合探测技术进行岩溶隧道超前预报研究,并将其应用于某新建铁路隧道。研究结果表明,地震反射法(HSP)与电磁波反射法(GPR)可互为补充,相互验证。地震联合反演在电阻率反演的帮助下能有效还原溶洞的大致形态与位置,同时低速界面内部波速形态更加均匀。对HSP探测结果中存在异常的里程范围,GPR法可用于进一步确定异常的规模和性质。通过对比验证和综合分析地下介质中多种物探参数(速度、介电/电阻率)的差异性,可获取隧道前方不良地质体的详细规模和可靠性质,从而识别和预测岩溶致灾构造和致灾模式。基于HSP-GPR联合探测技术的岩溶隧道超前预报研究为制定防治措施和建立监测系统提供了重要的支持和指导,可为类似岩溶隧道工程提供参考。

Feature Extraction and Classification of Echo Signal of Ground Penetrating Radar

Automatic feature extraction and classification algorithm of echo signal of ground penetrating radar is presented. Dyadic wavelet transform and the average energy of the wavelet coefficients are applied in this paper to decompose and extract feature of the echo signal. Then, the extracted feature vector is fed up to a feed forward muhi layer perceptron classifier. Experimental results based on the measured GPR, echo signals obtained from the Mei shan railway are presented.

Root imaging from ground penetrating radar data by CPSO-OMP compressed sensing

As the amount of data produced by ground penetrating radar （GPR） for roots is large, the transmission and the storage of data consumes great resources. To alleviate this problem, we propose here a root imaging algorithm using chaotic particle swarm optimal （CPSO） compressed sensing based on GPR data according to the sparsity of root space. Radar data are decomposed, observed, measured and represented in sparse manner, so roots image can be reconstructed with limited data. Firstly, radar signal measurement and sparse representation are implemented, and the solution space is established by wavelet basis and Gauss random matrix; secondly, the matching function is considered as the fitness function, and the best fitness value is found by a PSO algorithm; then, a chaotic search was used to obtain the global optimal operator; finally, the root image is reconstructed by the optimal operators. A-scan data, B-scan data, and complex data from American GSSI GPR is used, respectively, in the experimental test. For B-scan data, the computation time was reduced 60 % and PSNR was improved 5.539 dB; for actual root data imaging, the reconstruction PSNR was 26.300 dB, and total computation time was only 67.210 s. The CPSO-OMP algorithm overcomes the problem of local optimum trapping and comprehensively enhances the precision during reconstruction.

Modified Method for Estimating Organic Carbon Density in Discontinuous Karst Soil Using Ground-Penetrating Radar and Geostatistics

The conventional method which assumes the soil distribution is continuous was unsuitable for estimating soil organic carbon density(SOCD) in Karst areas because of its discontinuous soil distribution. The accurate estimation of SOCD in Karst areas is essential for carbon sequestration assessment in China. In this study, a modified method,which considers the vertical proportion of soil area in the profile when calculating the SOCD, was developed to estimate the SOCD in a typical Karst peak-cluster depression area in southwest China. In the modified method, ground-penetrating radar(GPR) technology was used to detect the distribution and thickness of soil. The accuracy of the method was confirmed through comparison with the data obtained using a validation method, in which the soil thickness was measured by excavation. In comparison with the conventional method and average-soil-depth method,the SOCD estimated using the GPR method showed the minimum relative error with respect to that obtained using the validation method. At a regional scale, the average SOCDs at depths of 0-20 cm and 0-100 cm, which were interpolated by ordinary kriging,were 1.49(ranging from 0.03-5.65) and 2.26(0.09-11.60) kgm-2based on GPR method in our study area(covering 393.6 hm2), respectively. Therefore, the modified method can be applied on the accurate estimation of SOCD in discontinuous soil areas such as Karst regions.

Finite difference time domain method forward simulation of complex geoelectricity ground penetrating radar model

The ground penetrating radar(GPR) forward simulation all aims at the singular and regular models, such as sandwich model, round cavity, square cavity, and so on, which are comparably simple. But as to the forward of curl interface underground or “v” figure complex model, it is difficult to realize. So it is important to forward the complex geoelectricity model. This paper takes two Maxwell’s vorticity equations as departure point, makes use of the principles of Yee’s space grid model theory and the basic principle finite difference time domain method, and deduces a GPR forward system of equation of two dimensional spaces. The Mur super absorbed boundary condition is adopted to solve the super strong reflection on the interceptive boundary when there is the forward simulation. And a self-made program is used to process forward simulation to two typical geoelectricity model.

Wigner Frequency Point Slice Analysis of Superposition Data for Phased-Array Ground Penetrating Radar

According to the frequency property of Phasedarray ground penetrating radar (PGPR), this paper gives a frequency point slice method based on Wigner time-frequency analysis. This method solves the problem of analysis for the PGPR's superposition data and makes detecting outcome simpler and detecting target more recognizable. At last, the analytical results of road test data of the Three Gorges prove the analytical method efficient. Key words phased-array ground penetrating radar - wigner time-frequency analysis - superposition data - object identification CLC number TN 715.7 Foundation item: Supported by the National Nature Science Foundation of China (50099620) and 863 Program Foundation of China (2001AA132050-03)Biography: ZOU Lian (1975-), male, Ph. D candidate, research direction: signal processing.

A NOVEL SVM FOR GROUND PENETRATING SYNTHETIC APERTURE RADAR LANDMINE DETECTION

The use of vehicle- or air-borne Ground Penetrating Synthetic Aperture Radar (GPSAR) to quickly detect landmines over large areas is becoming a trend. However, producing too many false alarms in GPSAR landmine detection is a major challenge in practical applications of GPSAR. Support Vector Machine (SVM), employing structural risk minimization theory, does not need large amounts of training data, which makes it suitable for solving the landmine detection problem. In this paper, a novel SVM with a hypersphere instead of a hyperplane classification boundary is proposed for landmine detection in GPSAR. The HyperSphere-SVM (HS-SVM) can be trained with both landmine and clutter data, or with landmine data only, which are called the two-class HS-SVM and the one-class HS-SVM, respectively. The HS-SVM has better generalization capability than the traditional HyperPlane-SVM (HP-SVM) with respect to varying operating conditions. Quantitative comparisons have been made using real data collected with the rail-GPSAR landmine detection system, which show that both the two-class and the one-class HS-SVMs have better detection performance than the HP-SVM.

Identifying soil structure along headwater hillslopes using ground penetrating radar based technique

Soil structure plays an important role in understanding soil attributes as well as hydrological processes. Effective method to obtain high quality soil map is therefore important for both soil science research and soil work ability improvement. However,traditional method such as digging soil pits is destructive and time-consuming. In this study, the structure of headwater hillslopes from Hemuqiao catchment(Taihu Basin, China) have been analyzed both by indirect(ground penetrating radar, GPR) and direct(excavation or soil auger) methods. Four transects at different locations of hillslopes in the catchment were selected for GPR survey. Three of them(#1, #2, and #3) were excavated to obtain fullscale soil information for interpreting radar images.We found that the most distinct boundary that can be detected by GPR is the boundary between soil and underlain bedrock. In some cases(e.g., 8-17 m in transect #2), in which the in situ soil was scarcely affected by colluvial process, different soil layers can be identified. This identification process utilized the sensitive of GPR to capture abrupt changes of soil characteristics in layer boundaries, e.g., surface organic layer(layer #1) and bamboo roots layer(layer#2, contain stone fragments), illuvial deposits layer(layer #3) and regolith layer(layer #4). However, in areas where stone fragments were irregularly distributed in the soil profile(highly affected bycolluvial and/or fluvial process), it was possible to distinguish which part contains more stone fragments in soil profile on the basis of reflection density(transect #3). Transect #4(unexcavated) was used to justify the GPR method for soil survey based on experiences from former transects. After that, O horizon thickness was compared by a hand auger.This work has demonstrated that GPR images can be of a potential data source for hydrological predictions.

基于曲波域凸集投影算法的缺失GPR信号高精度重建

受采集环境和仪器性能的影响,实测探地雷达(GPR)剖面中不可避免会出现部分信号缺失和坏道现象,易造成目标体产生的反射波和绕射波同相轴不连续,严重降低后续处理与成像精度和分辨率。为此,将图像处理中广泛应用的凸集投影(POCS)算法与具有良好稀疏特性的曲波变换相结合,提出了一种基于曲波域POCS算法的缺失GPR信号高精度重建方法。从压缩感知理论出发,建立了离散曲波变换基下缺失信号重建的目标函数,并采用POCS算法详细推导了缺失GPR信号重建的时间域迭代公式。其中,线性和指数迭代阈值模型用于更新曲波变换系数,从而高精度重建时间域缺失信号;平均绝对误差、信噪比、峰值信噪比用于定量评价GPR信号重建精度。模拟与实测GPR信号的重建试验表明:POCS算法可有效重建GPR剖面中的缺失信号;与线性阈值模型的POCS算法相比,指数阈值模型的POCS算法重建精度更高;与指数阈值模型的频率域POCS算法相比,指数阈值模型的曲波域POCS算法用于重建GPR剖面中连续多道缺失信号的误差更小、纵向伪影能量更弱,且对复杂GPR结构模型的缺失信号重建具有较强的适用性;与线性和指数阈值模型的频率域POCS算法、线性阈值模型的曲波域POCS算法相比,指数阈值模型的曲波域POCS重建方法的重建精度更高、平均绝对误差下降45%~99%、信噪比和峰值信噪比提高1~20 dB,其重建结果可为后续处理与解释提供高质量GPR信号。

Regional characteristics of sea ice thickness in Canadian shelf and Arctic Archipelago measured by Ground Penetrating Radar

Ground Penetrating Radar （GPR） measurements of sea ice thickness including undeformed ice and ridged ice were carried out in the central north Canadian Archipelago in spring 2010. Results have shown a significant spatial heterogeneity of sea ice thickness across the shelf. The undeformed multi-year fast ice of （2.05±0.09） m thick was investigated southern inshore zone of Borden island located at middle of the observational section, which was the observed maximum thickness in the field work. The less thick sea ice was sampled across a flaw lead with the thicknesses of （1.05±0.11） m for the pack ice and （1.24±0.13） m for the fast ice. At the northernmost spot of the section, the undeformed multi-year pack ice was （1.54±0.22） m thick with a ridged ice of 2.5 to 3 m, comparing to the multi-year fast ice with the thickness of （1.67±0.16） m at the southernmost station in the Prince Gustaf Adolf Sea.

基于GPR的巷道围岩空区探测及支护设计

为确保地下矿山掘进巷道围岩稳定性,发现前方不良地质体,采用地质雷达对掘进巷道围岩及底板进行空区探测,并对巷道围岩进行不同地应力作用下的稳定性分析,对不同长度锚杆加固后的锚杆轴力进行对比。结果表明:雷达探测的两个区域均出现不同深度的振幅较强反射区;1.5 m锚杆支护作用下围岩最大位移量分别减少39.3%和10.0%,X-有效应力分别增加42.8%和37.5%;1.5 m和1.8 m锚杆支护时轴力变化基本相同。根据同相轴的连续性对异常区进行判断,异常信号为充填不密实区及空洞,采用锚杆锚网喷浆支护。研究成果可以为类似矿山巷道围岩稳定性及支护提供借鉴意义。

Research on Data Combination for Phased-Array Ground Penetrating Radar

To resolve the data combination of Phased-array Ground Penetrating Radar (PAGPR), we first build a model of PAGPR and a layered model, and then a new data combination algorithm is presented based on it. This method calculates time delay of multi-receivers, basing on the signal of the nearest receiver, then shifts other signals and adds them up, and gets one signal at last. It has been proved that this method can restrain noise, multiple waves, clutter waves and improve the precision of time location. In the end, an example is given to prove the method's efficiency.