Automatic extraction of geometrical characteristics hidden in ground‐penetrating radar sectional images using simultaneous perturbation artificial bee colony algorithm

Ground‐penetrating radar is one of the most effective methods of detecting shallow buried objects. Ground‐penetrating radar radargram is a vertical map of the radar pulse reflections that returns from subsurface objects, and in the case of cylindrical objects, it would be a hyperbola. In order to get clear and accurate information on the presence, location, and geometry of the buried objects, the radargrams need to be interpreted. Interpretation of the results is a time‐consuming task and needs an expert with vast knowledge. Development of an automatic interpretation method of B‐scan ground‐penetrating radar images would be an effective and efficient solution to this problem. A novel automatic interpretation method of ground‐penetrating radar images, based on simultaneous perturbation artificial bee colony algorithm using tournament selection strategy, simultaneous perturbation stochastic approximation method, and new search equations, is introduced in this paper. The proposed algorithm is used to extract geometrical parameters, i.e. depth, location, and radius, of buried cylindrical objects in order to assess its accuracy. Synthetic data, simulated using GprMax2D forward modelling program, and real data, surveyed in the campus of Isfahan University of Technology, are used in the assessment. The performance of the proposed method in detecting synthetic hyperbolas is compared with that of the original artificial bee colony algorithm, genetic algorithm, and modified Hough transform. The results show superiority of the proposed algorithm, in detecting synthetic hyperbolas. Furthermore, the performance of the proposed method in estimating depth and radius of pipes in real ground‐penetrating radar images is compared with that of the modified Hough transform. The results indicate higher accuracy of the proposed method in estimating geometrical parameters of the buried cylindrical objects.     

机载探地雷达数值模拟及逆时偏移成像

机载探地雷达可以用于人类无法到达的危险地区、植被严重覆盖的地下目标体探测,然而由于机载探地雷达的特殊性,影响机载探地雷达探测效果的因素包括天线的极化方向、天线的飞行高度以及地表粗糙度等.为了研究这些影响因素与探测效果之间的关系,用三维时间域有限差分模拟电磁波的传播过程,以沙漠地区地下空洞掩体的机载探地雷达探测为实例,分别模拟了不同天线极化方向、天线高度及地表粗糙度情况下的机载探地雷达剖面,分析了各因素对机载探地雷达探测地下空洞目标体的影响.天线极化方向与目标体走向垂直更有利于地下目标体探测;天线距离地表越近,可以获得更高分辨率的雷达剖面;沙漠地表起伏越大,雷达剖面中的散射杂波能量越强,浅部地下目标体信号容易被掩盖.为了消除起伏地形造成的散射杂波,提出用逆时偏移成像技术对共炮集机载探地雷达数据进行偏移成像,成像结果优于基尔霍夫偏移成像结果.     

地质雷达在公路滑坡加固治理中的应用

地质雷达能快速、准确地探测地下潜在的地质缺陷体的空间位置、形状大小及电性质等其他一些地质参数,可以为滑坡的加固设计、施工提供可靠的资料,简述了地质雷达的勘探原理和方法,并以实例说明了地质雷达在滑坡治理中的应用方法及效果。     

多相离散随机介质模型及其探地雷达波场特征研究

沥青混凝土是由骨料、沥青胶浆、空气按照一定的体积百分比混合而成的多相非匀质混合物,其骨料、沥青胶浆和空气的体积不等、形状各异、介电特性不同、空间位置随机分布,具有明显的多相、离散、随机介质特征.本文基于随机介质模型理论,(1)测量与统计了介电常数在典型沥青混凝土芯样空间上的随机分布统计特征;(2)估算了沥青混凝土介质的自相关函数及其特征参数(自相关长度、自相关角度等),确定其随机介质类型;(3)提出了量化约束下的多相离散随机介质建模算法,以混合型椭圆自相关函数为基础,构建了不同粗糙度因子的多相离散随机介质模型;(4)构建了不同空隙率的多相离散随机介质模型,正演模拟与对比分析了探地雷达波在均匀介质、连续型随机介质和多相离散随机介质中的传播特征.结果表明:多相离散随机介质模型不仅描述了沥青混凝土的多相、离散与空间随机分布统计特征,而且进一步描述了其各组成物质体积百分比,能更全面、准确地描述沥青混凝土的介质特征,同时也为描述其他类似材料或介质提供了新的方法和途径;在多相离散随机介质模型中,探地雷达波散射强烈,随机、无序传播的散射波相互叠加干涉,形成了明显的随机扰动和"噪声",致使异常体反射波扭曲变形、不连续,降低了探地雷达回波的信噪比和分辨率.研究探地雷达波的随机扰动特征与多相离散随机介质模型参数之间的关系,将为定量评价多相离散随机介质的属性参数提供参考和帮助.     

A three dimensional approach for tracking cracks in bridges using GPR

Corrosion associated with reinforcing bars is the most significant contributor to bridge deficiencies. The corrosion is usually caused by moisture and chloride ion exposure. The reinforcing bars are attacked by corrosion and yield expansive corrosion products. These oxidation products occupy a larger volume than the original intact steel and internal expansive stresses lead to cracking and debonding. There are some conventional inspection methods for the detection of the reinforcing bar's corrosion but they can be invasive and destructive, often laborious, and lane closure is required and it is difficult or unreliable for any quantification of corrosion. For these reasons, bridge engineers always prefer more to use the ground penetrating radar (GPR) technique. In this work a novel numerical approach for three dimensional tracking and mapping of cracks in the bridge is proposed. The work starts from some interesting results based on the use of the 3D imaging technique in order to improve the potentiality of the GPR to detect voids, cracks or buried objects. The numerical approach has been tested on data acquired on a bridge by using a pulse GPR system specifically designed for bridge deck and pavement inspection. The equipment integrates two arrays of Ultra Wide Band ground coupled antennas, having a main working frequency of 2 GHz. The two arrays are using antennas arranged with a different polarization. The cracks, associated often to moisture increase and higher values of the dielectric constant, produce a not negligible increase of the signal amplitude. Following this, the algorithm, organized in preprocessing, processing and postprocessing stages, analyzes the signal by comparing the value of the amplitude all over the domain of the radar scan.     

EM target location1

We consider the problem of computing the most probable location of a target based on radar measurements of the subsurface. Our algorithm makes use of the maximum likelihood estimator (MLE), which represents a correlation between the measured data and synthetic data generated for the object of interest at different locations. Previous studies assume a plane-wave acquisition geometry and target object(s) embedded in a uniform background. In this paper, a generalization of the MLE method is presented which is valid for discrete point sources (and receivers) and a 2D model (i.e. a 2.5D acquisition geometry). Within this formulation the treatment of a non-uniform background model is also possible. We concentrate on geotechnical ground investigations and assume that the characteristic dimensions of the target object are in the range 1–2λ, (λ being the wavelength). The potential of the method is demonstrated employing cross-hole radar data acquired in a controlled field experiment. The MLE result is also compared with the image obtained employing a full reconstruction method such as diffraction tomography.     

地质雷达技术在巴彦查干地区地震勘探中的应用

简要介绍地质雷达技术原理，利用大庆探区巴彦查干地区地质雷达实测资料进行解释，并结合微测井资料进行地区地震波表层层速度的教育处和静校正量的提取。结果表明，地质雷达能获得连续浅下地剖面，可弥补微测井资料的不足，因而在地震勘探表层地质调查和静校正量提取等方法方面上的有实际应用价值。     

Application of Ground Penetrating Radar Surveys and GPS Surveys for Monitoring the Condition of Levees and Dykes

This paper analyses the possibility of using integrated GPS (Global Positioning System) surveys and ground penetrating radar surveys to precisely locate damages to levees, particularly due to the activity of small fossorial mammals. The technology of intercommunication between ground penetrating radar (GPR) and an RTK (Real-Time Kinematic) survey unit, and the method of data combination, are presented. The errors which may appear during the survey work are also characterized. The procedure for processing the data so that the final results have a spatial character and are ready to be implemented in digital maps and geographic information systems (GIS) is also described.     

Theoretical seismogram constraints on some crustal velocity models in the central United States

Summary Earthquake investigations in the central United States require a realistic crustal model for accurate location of seismic events, for the determination of earthquake source parameters, and for theoretical ground motion prediction for an assumed earthquake source. A number of crustal models have been proposed which were based on first arrival refraction data obtained from artificial and natural seismic sources.The reflectivity method for generating realistic theoretical seismograms is used together with recently acquired refraction survey data to distinguish among several of the proposed crustal models. The data used in this study preclude a definitive statement about the nature of the lower crust in the region. However, a crust with two or more layers in the upper 20 km immediately below the basement is preferred. The absence of prominent near yertical reflections suggests that the layers may be separated by rapid velocity gradients rather than by sharp discontinuities.     

Cost‐effective non‐metric photogrammetry from consumer‐grade sUAS: implications for direct georeferencing of structure from motion photogrammetry

The declining costs of small Unmanned Aerial Systems (sUAS), in combination with Structure‐from‐Motion (SfM) photogrammetry have triggered renewed interest in image‐based topography reconstruction. However, the potential uptake of sUAS‐based topography is limited by the need for ground control acquired with expensive survey equipment. Direct georeferencing (DG) is a workflow that obviates ground control and uses only the camera positions to georeference the SfM results. However, the absence of ground control poses significant challenges in terms of the data quality of the final geospatial outputs. Notably, it is generally accepted that ground control is required to georeference, refine the camera calibration parameters, and remove any artefacts of optical distortion from the topographic model. Here, we present an examination of DG carried out with low‐cost consumer‐grade sUAS. We begin with a study of surface deformations resulting from systematic perturbations of the radial lens distortion parameters. We then test a number of flight patterns and develop a novel error quantification method to assess the outcomes. Our perturbation analysis shows that there exists families of predictable equifinal solutions of K₁‐K₂ which minimize doming in the output model. The equifinal solutions can be expressed as K₂ = f (K₁) and they have been observed for both the DJI Inspire 1 and Phantom 3 sUAS platforms. This equifinality relationship can be used as an external reliability check of the self‐calibration and allow a DG workflow to produce topography exempt of non‐affine deformations and with random errors of 0.1% of the flying height, linear offsets below 10 m and off‐vertical tilts below 1°. Whilst not yet of survey‐grade quality, these results demonstrate that low‐cost sUAS are capable of producing reliable topography products without recourse to expensive survey equipment and we argue that direct georeferencing and low‐cost sUAS could transform survey practices in both academic and commercial disciplines. Copyright © 2016 John Wiley & Sons, Ltd.     

随机方法在地震烈度速报中的应用

我国地震监测台网间距大,很难实现大震发生时地震烈度分布图的快速编制.基于随机方法,利用历史小震数据反演地震动估计模型的参数,参考地震发生时获取的少量强震动数据,选取合适的震源参数,正演地震动场的分布.根据地震烈度与地震动参数的经验关系,实现地震烈度速报.本方法可以模拟大震的近断层地震动特征,对高烈度区的判断较目前常用的烈度速报方法更为合理.研究成果既可以用于首张烈度分布图的发布,还能够用于地震烈度的动态修正.     

Snow Mass Quantification and Avalanche Victim Search by Ground Penetrating Radar

Ground penetrating radar (GPR) systems can be used in many applications of snow and ice research. The information from the GPR is used to identify and interpret layers, objects and different structures in the snow. A commercially available GPR system was further developed to work in the rough environment of snow and ice. The applied GPR is a 900 MHz system that easily reaches snow depths of up to 10 meters. The system was calibrated in the course of several manual snow depth measurements during each survey. The depth resolution depends on the snow type and is around ±0.1 m. The GPR system is carried alongside a line of interest and is triggered by an odometer wheel at regular adjustable steps. All equipment is mounted in a sledge and is pulled by a snowmobile over the snow surface. This setup allows for an efficient coverage of several kilometers of terrain profiles. The radar profiles give a real time two-dimensional impression of structures and objects and the interface between snow and the underlying ground. The actual radar profile is shown on a screen on the sledge allowing the immediate marking of objects and structures. During the past three years the instrument was successfully used for the study of snow distributions, for the detection of glacier crevasses under the snow cover, and for the search of avalanche victims in avalanche debris. The results show the capability of the instrument to detect persons and objects in the snow cover. In the future, this device may be a new tool for avalanche rescue operations. Today, the size and weight of the system prevents the accessing of very steep slopes and areas not accessible to snowmobiles. Further developments will decrease the size of the system and make it a valuable tool to quantify snow masses in avalanche release zones and run-out areas.     

Inversion of HF backscatter ionograms using elevation scans

Accuracy in target location by over-the-horizon radar (OTHR) can be improved when the propagation channel is known. An inversion method able to provide an equivalent electron density profile of the ionosphere from backscatter ionograms is presented in this paper. The method uses the measurements realized by the radar during elevation scans. One difficulty when using measured data is the presence of outliers and, moreover, the lack of data for low elevation and for high elevation angle. The method presented here tries to overcome these difficulties. At the end, the inversion provides parameters of an equivalent ionosphere that can be used to characterize the propagation and to convert group path into ground range.     

相交早第四纪断裂近断层地震动场预测——以枣庄市新城区为例

近断层地震动场的预测不仅可以为抗震结构设计提供更加丰富的地震动输入,也可以作为土地合理规划的参考依据。在一些地震活动相对较弱的地区,地震往往发生在两个早第四纪断裂相交的位置处。因此对于这种相交早第四纪断裂区的近断层地震动场预测具有实际的意义。本文以枣庄市新城区为例,预测了在设定地震发生时,相交早第四纪断裂近断层地震动场的分布情况。先分别计算了近断层区低频和高频的地震动,然后将低频和高频成分合成宽频带的地震动场。在计算低频地震动场时,建立了枣庄市新城区地下三维传播介质模型和震源模型。计算的过程是模拟震源发生破裂产生地震波后,地震波在地下介质中的传播过程。使用了三维显式有限元、快速拉格朗日有限元法等数值计算方法以及并行计算技术来提高计算的速度。由于地震动的频率成分是连续的,因此对于高频地震动使用了随机震动理论来进行合成。本文研究的预测结果具备断层附近地震动的一些最基本的特征,符合当前对断层附近地震动的基本认识。     

Stochastic simulation of regionalized ground motions using wavelet packets and cokriging analysis

Performance‐based earthquake engineering often requires ground‐motion time‐history analyses to be performed, but very often, ground motions are not recorded at the location being analyzed. The present study is among the first attempt to stochastically simulate spatially distributed ground motions over a region using wavelet packets and cokriging analysis. First, we characterize the time and frequency properties of ground motions using the wavelet packet analysis. The spatial cross‐correlations of wavelet packet parameters are determined through geostatistical analysis of regionalized ground‐motion data from the Northridge and Chi‐Chi earthquakes. It is observed that the spatial cross‐correlations of wavelet packet parameters are closely related to regional site conditions. Furthermore, using the developed spatial cross‐correlation model and the cokriging technique, wavelet packet parameters at unmeasured locations can be best estimated, and regionalized ground‐motion time histories can be synthesized. Case studies and blind tests using data from the Northridge and Chi‐Chi earthquakes demonstrate that the simulated ground motions generally agree well with the actual recorded data. The proposed method can be used to stochastically simulate regionalized ground motions for time‐history analyses of distributed infrastructure and has important applications in regional‐scale hazard analysis and loss estimation. Copyright © 2014 John Wiley & Sons, Ltd.     

Radar rainfall uncertainty modelling influenced by wind

Radar‐based estimates of rainfall are affected by many sources of uncertainties, which would propagate through the hydrological model when radar rainfall estimates are used as input or initial conditions. An elegant solution to quantify these uncertainties is to model the empirical relationship between radar measurements and rain gauge observations (as the ‘ground reference’). However, most current studies only use a fixed and uniform model to represent the uncertainty of radar rainfall, without consideration of its variation under different synoptic regimes. Wind is such a typical weather factor, as it not only induces error in rain gauge measurements but also causes the raindrops observed by weather radar to drift when they reach the ground. For this reason, as a first attempt, this study introduces the wind field into the uncertainty model and designs the radar rainfall uncertainty model under different wind conditions. We separate the original dataset into three subsamples according to wind speed, which are named as WDI (0–2 m/s), WDII (2–4 m/s) and WDIII (>4 m/s). The multivariate distributed ensemble generator is introduced and established for each subsample. Thirty typical events (10 at each wind range) are selected to explore the behaviours of uncertainty under different wind ranges. In each time step, 500 ensemble members are generated, and the values of 5th to 95th percentile values are used to produce the uncertainty bands. Two basic features of uncertainty bands, namely dispersion and ensemble bias, increase significantly with the growth of wind speed, demonstrating that wind speed plays a considerable role in influencing the behaviour of the uncertainty band. On the basis of these pieces of evidence, we conclude that the radar rainfall uncertainty model established under different wind conditions should be more realistic in representing the radar rainfall uncertainty. This study is only a start in incorporating synoptic regimes into rainfall uncertainty analysis, and a great deal of more effort is still needed to build a realistic and comprehensive uncertainty model for radar rainfall data. Copyright © 2014 John Wiley & Sons, Ltd.     

Estimation of the 3D correlation structure of an alluvial aquifer from surface-based multi-frequency ground-penetrating radar reflection data

Knowledge about the stochastic nature of heterogeneity in subsurface hydraulic properties is critical for aquifer characterization and the corresponding prediction of groundwater flow and contaminant transport. Whereas the vertical correlation structure of the heterogeneity is often well constrained by borehole information, the lateral correlation structure is generally unknown because the spacing between boreholes is too large to allow for its meaningful inference. There is, however, evidence to suggest that information on the lateral correlation structure may be extracted from the correlation statistics of the subsurface reflectivity structure imaged by surface-based ground-penetrating radar measurements. To date, case studies involving this approach have been limited to 2D profiles acquired at a single antenna centre frequency in areas with limited complementary information. As a result, the practical reliability of this methodology has been difficult to assess. Here, we extend previous work to 3D and consider reflection ground-penetrating radar data acquired using two antenna centre frequencies at the extensively explored and well-constrained Boise Hydrogeophysical Research Site. We find that the results obtained using the two ground-penetrating radar frequencies are consistent with each other, as well as with information from a number of other studies at the Boise Hydrogeophysical Research Site. In addition, contrary to previous 2D work, our results indicate that the surface-based reflection ground-penetrating radar data are not only sensitive to the aspect ratio of the underlying heterogeneity, but also, albeit to a lesser extent, to the so-called Hurst number, which is a key parameter characterizing the local variability of the fine-scale structure.     

Evaluation of trenching,ground penetrating radar (GPR) and electrical resistivity tomography (ERT) for sinkhole characterization

This paper explores the suitability and advantages of combining the trenching technique with geophysical surveys [ground penetrating radar (GPR) and electrical resistivity tomography (ERT)] for sinkhole characterization in a mantled karst area. The approach is applied to two active sinkholes concealed by anthropogenic deposits and formed by contrasting subsidence mechanisms; collapse and sagging. The ERT section acquired across the collapse sinkhole images the clayey fill of the depression as an obvious low resistivity area, showing the approximate location of the sinkhole edges. Spatially dense GPR surveys provide information on the position of the boundaries of the concealed subsidence structures and their three‐dimensional (3D) internal geometry, revealing the dominant subsidence mechanism. We illustrate the impact of several factors on the quality of the GPR data such as sinkhole size, nominal frequency of the antennas, antenna shielding, and the presence of backfilled excavations and above‐surface objects. Trenches provided detailed information on the subsurface structure of the sinkhole, subsidence magnitude, partitioning of the strain, and the position of the sinkhole edges, especially when they are deep enough and excavated across the central sector and perpendicular to the boundaries. The stratigraphic and structural relationships observed in the trench were then used to infer the spatial evolution of the sinkholes (e.g. enlargement), their kinematic behavior (episodic versus progressive), and to differentiate discrete subsidence events and their associated magnitude. Numerical dates were used to estimate average subsidence rates and the recurrence of subsidence events. Such integrated data sets may be used as an objective basis to forecast the future behavior of potentially damaging sinkholes and to assess the associated hazard and risk. Copyright © 2013 John Wiley & Sons, Ltd.